BC BUSINESS
Saved by @jay_millerjay

Time for #PapersThatMakeYouGoHmmm! A weekly summary of new ML papers from arXiv that make me think one or more of:

1. That looks useful!
2. That's an interesting approach!
3. A business could be built around this!
4. How did they do that?!

 Integrating prediction in mean-variance portfolio optimization

https://t.co/QWaryyQzam
Corporate Social Responsibility and Corporate Governance: A cognitive approach

https://t.co/7S7MkxrJEH
The Gender Pay Gap Revisited with Big Data: Do Methodological Choices Matter?

https://t.co/ykUEv6isZQ
Sustainable and Resilient Systems for Intergenerational Justice

https://t.co/1pPKDEh85z
A Core of E-Commerce Customer Experience based on Conversational Data using Network Text Methodology

https://t.co/2CgOY7mZH9
Deep Learning for Market by Order Data

https://t.co/Nzs544G9ST
The economic dependency of the Bitcoin security

https://t.co/UxdJQn9HKg
On Technical Trading and Social Media Indicators in Cryptocurrencies' Price Classification Through Deep Learning

https://t.co/f53jC2V5cz
LATE for History

https://t.co/lLy6UBfMvc
Supportive 5G infrastructure policies are essential for universal 6G: Evidence from an open-source techno-economic simulation model using remote sensing

https://t.co/1WMHwXyhtT
Integrating Floor Plans into Hedonic Models for Rent Price Appraisal

https://t.co/01tmCxtBpg
Personality Traits and the Marriage Market

https://t.co/JiXL2IJPxd
Time-varying properties of asymmetric volatility and multifractality in Bitcoin

https://t.co/rTtGE7PUe8
REST: Relational Event-driven Stock Trend Forecasting

https://t.co/FDAoNZgxNd
How Misuse of Statistics Can Spread Misinformation: A Study of Misrepresentation of COVID-19 Data

https://t.co/yisQnqgax1
Aggregate Modeling and Equilibrium Analysis of the Crowdsourcing Market for Autonomous Vehicles

https://t.co/VVnZYkLenh
The corruptive force of AI-generated advice

https://t.co/JxplsShpnJ
The Golden Age of the Mathematical Finance

https://t.co/5UWtrMLuFX
Deep Reinforcement Learning for Portfolio Optimization using Latent Feature State Space (LFSS) Module

https://t.co/9210MxNh8Y
Hedging of Financial Derivative Contracts via Monte Carlo Tree Search

https://t.co/Zrj7YsDivl
Optimising Long-Term Outcomes using Real-World Fluent Objectives: An Application to Football

https://t.co/ArOFaGcoIK
SLAKE: A Semantically-Labeled Knowledge-Enhanced Dataset for Medical Visual Question Answering

https://t.co/587J7vurn6
Clockwork Variational Autoencoders for Video Prediction

https://t.co/CnLG5iFFCv
Gifsplanation via Latent Shift: A Simple Autoencoder Approach to Progressive Exaggeration on Chest X-rays

https://t.co/fwycwMG0We
Fake News Detection: a comparison between available Deep Learning techniques in vector space

https://t.co/jGPmEwwKnU
ELIXIR: Learning from User Feedback on Explanations to Improve Recommender Models

https://t.co/Vq6GK26YUm
L2E: Learning to Exploit Your Opponent

https://t.co/mj1wN8FwVd
A Study on the Manifestation of Trust in Speech

https://t.co/GiE4b80x7R
AI Can Stop Mass Shootings, and More

https://t.co/zfHlij5ZNz
Reinforcement Learning for Datacenter Congestion Control

https://t.co/3egxwyn3Td
FIXME: Enhance Software Reliability with Hybrid Approaches in Cloud

https://t.co/brnJt0ITk6
Training Microsoft News Recommenders with Pretrained Language Models in the Loop

https://t.co/OEa0iH5JFo
Unsupervised Clustering of Time Series Signals using Neuromorphic Energy-Efficient Temporal Neural Networks

https://t.co/ZhrOxKJx7W
From Extreme Multi-label to Multi-class: A Hierarchical Approach for Automated ICD-10 Coding Using Phrase-level Attention

https://t.co/2WwpmBUXiX
Entity-level Factual Consistency of Abstractive Text Summarization

https://t.co/7a18lXQw8B
Understanding and Creating Art with AI: Review and Outlook

https://t.co/qxd7lLqSJo
Spacewalker: Rapid UI Design Exploration Using Lightweight Markup Enhancement and Crowd Genetic Programming

https://t.co/x4jo8hbIDX
Deep Learning Approaches for Forecasting Strawberry Yields and Prices Using Satellite Images and Station-Based Soil Parameters

https://t.co/quFFINIoVd
Towards AIOps in Edge Computing Environments

https://t.co/Bq1vusI0jJ
BEDS: Bagging ensemble deep segmentation for nucleus segmentation with testing stage stain augmentation

https://t.co/j19fLyb9Oz
Genetically Optimized Prediction of Remaining Useful Life

https://t.co/J9vxC5PNRl
An Objective Laboratory Protocol for Evaluating Cognition of Non-Human Systems Against Human Cognition

https://t.co/g3qsoxcZKt
Knowledge discovery from emergency ambulance dispatch during COVID-19: A case study of Nagoya City, Japan

https://t.co/oh7Qm5F7i0
Towards an AI Coach to Infer Team Mental Model Alignment in Healthcare

https://t.co/mG86vPY2pI
Towards the Right Kind of Fairness in AI

https://t.co/BE20tyAGpf
Sparsely Factored Neural Machine Translation

https://t.co/sZDUaClW1X
I Want This Product but Different : Multimodal Retrieval with Synthetic Query Expansion

https://t.co/YtxVyTI6sc
A Graph Neural Network to Model User Comfort in Robot Navigation

https://t.co/oq35Ada9gS
Using exoskeletons to assist medical staff during prone positioning of mechanically ventilated COVID-19 patients: a pilot study

https://t.co/sTUIYEztwW
Autonomous Navigation in Dynamic Environments: Deep Learning-Based Approach

https://t.co/XViAqjhCwJ
Formation of Social Ties Influences Food Choice: A Campus-Wide Longitudinal Study

https://t.co/iMMa4QxAtj
ACTA: A Mobile-Health Solution for Integrated Nudge-Neurofeedback Training for Senior Citizens

https://t.co/5jV6U6GAhc
Fully General Online Imitation Learning

https://t.co/0RHhj8SI8K
Temporal Memory Attention for Video Semantic Segmentation

https://t.co/6L5gZP2EOx
On the Post-hoc Explainability of Deep Echo State Networks for Time Series Forecasting, Image and Video Classification

https://t.co/OcKtSHWG0U
Beyond Fully-Connected Layers with Quaternions: Parameterization of Hypercomplex Multiplications with $1/n$ Parameters

https://t.co/l6AvMftn6F
Ensemble Transfer Learning of Elastography and B-mode Breast Ultrasound Images

https://t.co/TpYMFLpTva
Mode-Assisted Joint Training of Deep Boltzmann Machines

https://t.co/aEML9if9sE
Integrating Pre-trained Model into Rule-based Dialogue Management

https://t.co/0yqJvEZcyH
Reward Poisoning in Reinforcement Learning: Attacks Against Unknown Learners in Unknown Environments

https://t.co/V7cvV7ImjK
TableLab: An Interactive Table Extraction System with Adaptive Deep Learning

https://t.co/x431QLmZlU
A Cooperative Memory Network for Personalized Task-oriented Dialogue Systems with Incomplete User Profiles

https://t.co/p9nFs0U9me
The Yin-Yang dataset

https://t.co/L1yG0OWPHX
Music Harmony Generation, through Deep Learning and Using a Multi-Objective Evolutionary Algorithm

https://t.co/HZQT4Kqc1D
ResNet-LDDMM: Advancing the LDDMM Framework Using Deep Residual Networks

https://t.co/FQXH2WrGRG
GraphGallery: A Platform for Fast Benchmarking and Easy Development of Graph Neural Networks Based Intelligent Software

https://t.co/c81dEIgiuT
Engineering Education in the Age of Autonomous Machines

https://t.co/sJcOhKpDIe
What Do We Want From Explainable Artificial Intelligence (XAI)? -- A Stakeholder Perspective on XAI and a Conceptual Model Guiding Interdisciplinary XAI Research

https://t.co/MJZgPvBSlz
Hierarchical VAEs Know What They Don't Know

https://t.co/6vJN2v1XHd
An AutoML-based Approach to Multimodal Image Sentiment Analysis

https://t.co/VWRIp1e8is
Boosting Deep Transfer Learning for COVID-19 Classification

https://t.co/A5f6F2jpug
Steadily Learn to Drive with Virtual Memory

https://t.co/xm05d92wqs
On the use of generative deep neural networks to synthesize artificial multichannel EEG signals

https://t.co/61zKdEpX0Y
EDITH :ECG biometrics aided by Deep learning for reliable Individual auTHentication

https://t.co/jPhEInmm5B
Training Stacked Denoising Autoencoders for Representation Learning

https://t.co/uKTsoKDKgC
TransFuse: Fusing Transformers and CNNs for Medical Image Segmentation

https://t.co/SARCnpNwAg
Training Larger Networks for Deep Reinforcement Learning

https://t.co/gzAKBfNcdS
Anomalous Sound Detection with Machine Learning: A Systematic Review

https://t.co/yLk3RbxOOm
How RL Agents Behave When Their Actions Are Modified

https://t.co/lrc27s8s7S
Diverse Auto-Curriculum is Critical for Successful Real-World Multiagent Learning Systems

https://t.co/NRC8Q1Dk4w
Player-Centered AI for Automatic Game Personalization: Open Problems

https://t.co/mSfmztneSi
Jira: a Kurdish Speech Recognition System Designing and Building Speech Corpus and Pronunciation Lexicon

https://t.co/YLBVXgk79P
AI Ethics Needs Good Data

https://t.co/DAtB3CfLzm
Why Talking about ethics is not enough: a proposal for Fintech's AI ethics

https://t.co/IuZxZoRKyK
Sequential Recommendation in Online Games with Multiple Sequences, Tasks and User Levels

https://t.co/CipbumMwLh
Fast End-to-End Speech Recognition via a Non-Autoregressive Model and Cross-Modal Knowledge Transferring from BERT

https://t.co/amS3PWqZOS
CHARET: Character-centered Approach to Emotion Tracking in Stories

https://t.co/gIbPb48kio
DAC: Deep Autoencoder-based Clustering, a General Deep Learning Framework of Representation Learning

https://t.co/TKLt9iu2Nz
Reinforcement Learning for IoT Security: A Comprehensive Survey

https://t.co/e2F4maHr4a
Resilient Machine Learning for Networked Cyber Physical Systems: A Survey for Machine Learning Security to Securing Machine Learning for CPS

https://t.co/32rYU1TZZW
Domain Adversarial Reinforcement Learning

https://t.co/JSBY6Vb2M1
Learning Intents behind Interactions with Knowledge Graph for Recommendation

https://t.co/OY8vxtBIOY
Adversarial defense for automatic speaker verification by cascaded self-supervised learning models

https://t.co/qqi8RuilnA
PAQ: 65 Million Probably-Asked Questions and What You Can Do With Them

https://t.co/PXRVg4qvxf
Interactive Learning from Activity Description

https://t.co/31YbQLZQvJ
DeepRA: Predicting Joint Damage From Radiographs Using CNN with Attention

https://t.co/wG0zctmbTq
Improving Automated Visual Fault Detection by Combining a Biologically Plausible Model of Visual Attention with Deep Learning

https://t.co/yyD2nuVTfu
Multi-class Generative Adversarial Nets for Semi-supervised Image Classification

https://t.co/ezwaLcp6Ga
Wasserstein Proximal of GANs

https://t.co/gu8E7HcGaX
Universal Adversarial Perturbations for Malware

https://t.co/hmykJNnJje
Towards Robust Visual Information Extraction in Real World: New Dataset and Novel Solution

https://t.co/pt4JfjyLCJ
A novel method for object detection using deep learning and CAD models

https://t.co/79JfZ0nLpj
Intelligent Software Web Agents: A Gap Analysis

https://t.co/92pGGLfKEp
VitrAI -- Applying Explainable AI in the Real World

https://t.co/Nn9YeUsVx0
Rethinking Eye-blink: Assessing Task Difficulty through Physiological Representation of Spontaneous Blinking

https://t.co/Qjl0MJ5Vf7
Exploiting Spline Models for the Training of Fully Connected Layers in Neural Network

https://t.co/uKVPq84EfT
Improving Object Detection in Art Images Using Only Style Transfer

https://t.co/pXbPIx0jQu
Transformer Language Models with LSTM-based Cross-utterance Information Representation

https://t.co/RlboGXdizN
A Decentralized Approach Towards Responsible AI in Social Ecosystems

https://t.co/x4VivBrgwH
DEEPF0: End-To-End Fundamental Frequency Estimation for Music and Speech Signals

https://t.co/eKGz0hAxXO
Therapeutics Data Commons: Machine Learning Datasets and Tasks for Therapeutics

https://t.co/wAHnPiA6wC
A Machine Learning model of the combination of normalized SD1 and SD2 indexes from 24h-Heart Rate Variability as a predictor of myocardial infarction

https://t.co/8LEjDbAXNp
Recurrent Rational Networks

https://t.co/QsVaicMeu2
Robust PDF Document Conversion Using Recurrent Neural Networks

https://t.co/GmRrxe5Qiv
VAE Approximation Error: ELBO and Conditional Independence

https://t.co/fTzOCBiLWX
DINO: A Conditional Energy-Based GAN for Domain Translation

https://t.co/qp0cOgm03Q
A Mathematical Principle of Deep Learning: Learn the Geodesic Curve in the Wasserstein Space

https://t.co/VJSUzwRcXF
Less is More: Pre-training a Strong Siamese Encoder Using a Weak Decoder

https://t.co/kSqin9QLdn
Improving Hierarchical Adversarial Robustness of Deep Neural Networks

https://t.co/mC7Cvg1PcF
Domain Adaptation for Medical Image Analysis: A Survey

https://t.co/eJBBMJnI5D
Regular Expressions for Fast-response COVID-19 Text Classification

https://t.co/6Eaw9HE42k
Transfer Learning for Linear Regression: a Statistical Test of Gain

https://t.co/VjvcLRo4Ir
DeeperForensics Challenge 2020 on Real-World Face Forgery Detection: Methods and Results

https://t.co/l9QrkIu3ir
Enhanced Magnetic Resonance Image Synthesis with Contrast-Aware Generative Adversarial Networks

https://t.co/PQkL2XhIG8
NFCNN: Toward a Noise Fusion Convolutional Neural Network for Image Denoising

https://t.co/fhBNkwq8PX
A Comprehensive Review of Deep Learning-based Single Image Super-resolution

https://t.co/fsork7CxTr
Dynamic Memory based Attention Network for Sequential Recommendation

https://t.co/o9t1FXypki
Sparse-Interest Network for Sequential Recommendation

https://t.co/MS5CI0w4LL
ADOM: Accelerated Decentralized Optimization Method for Time-Varying Networks

https://t.co/Vbdrsxve7a
Deep Neural Networks based Invisible Steganography for Audio-into-Image Algorithm

https://t.co/gw8Wlpw3ex
Quiz-Style Question Generation for News Stories

https://t.co/NUYssrgmSd
TapNet: The Design, Training, Implementation, and Applications of a Multi-Task Learning CNN for Off-Screen Mobile Input

https://t.co/rMIymn4dfQ
Towards Adversarial-Resilient Deep Neural Networks for False Data Injection Attack Detection in Power Grids

https://t.co/vh8GvCY6Zl
End-to-end learnable EEG channel selection with deep neural networks

https://t.co/pKRFwib7LH
How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models

https://t.co/4M9GlITBJG
POLA: Online Time Series Prediction by Adaptive Learning Rates

https://t.co/LSTQo0zQlj
Graph Learning with 1D Convolutions on Random Walks

https://t.co/bmXrLWx5rk
Preventing Posterior Collapse Induced by Oversmoothing in Gaussian VAE

https://t.co/PumNHJh5QZ
Rethinking Co-design of Neural Architectures and Hardware Accelerators

https://t.co/pWkCQtXuaB
Centroid Transformers: Learning to Abstract with Attention

https://t.co/d5RvbJ4j0E
Firefly Neural Architecture Descent: a General Approach for Growing Neural Networks

https://t.co/FzRFIJP7UK
Re-identification of Individuals in Genomic Datasets Using Public Face Images

https://t.co/cGC3CLWttM
Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications

https://t.co/rxJWi0F0mK
Globally-Robust Neural Networks

https://t.co/ypdG6K1yxq
Scaling Neuroscience Research using Federated Learning

https://t.co/CYfMhiOFAU
Complex Momentum for Learning in Games

https://t.co/t4pROL50V1
Cross-SEAN: A Cross-Stitch Semi-Supervised Neural Attention Model for COVID-19 Fake News Detection

https://t.co/vpCq4UiEsm
DESED-FL and URBAN-FL: Federated Learning Datasets for Sound Event Detection

https://t.co/YnfdONIDDQ
Accelerated Simulations of Molecular Systems through Learning of their Effective Dynamics

https://t.co/wPptFLMYkf
Variational Autoencoder for Speech Enhancement with a Noise-Aware Encoder

https://t.co/Z5vy8ttfaT
CheXternal: Generalization of Deep Learning Models for Chest X-ray Interpretation to Photos of Chest X-rays and External Clinical Settings

https://t.co/YhMIEtAv34
Coupled Feature Learning for Multimodal Medical Image Fusion

https://t.co/odDT1nMCZY
LambdaNetworks: Modeling Long-Range Interactions Without Attention

https://t.co/5Nxb3BOo3d
Evolving GAN Formulations for Higher Quality Image Synthesis

https://t.co/EatFRyBMbv
End-to-end lyrics Recognition with Voice to Singing Style Transfer

https://t.co/xMM0gL8CdX
Deep Neural Network Based Differential Equation Solver for HIV Enzyme Kinetics

https://t.co/Zd0n1kYr2e
Prioritizing Original News on Facebook

https://t.co/gUWAWGu1TC
Topological Obstructions to Autoencoding

https://t.co/weK3WN6AQm
Interpretable COVID-19 Chest X-Ray Classification via Orthogonality Constraint

https://t.co/z8C1xWOz27
Topological Deep Learning: Classification Neural Networks

https://t.co/BK6OEZgjqe
GradInit: Learning to Initialize Neural Networks for Stable and Efficient Training

https://t.co/e2rZM5IFaV
A Survey of Machine Learning for Computer Architecture and Systems

https://t.co/AgmBfoG2Ku
Inverse Reinforcement Learning in the Continuous Setting with Formal Guarantees

https://t.co/3S57gdjDPe
Few-Shot Graph Learning for Molecular Property Prediction

https://t.co/i6BjHPlKRo
A Koopman Approach to Understanding Sequence Neural Models

https://t.co/NKXebVYsxL
Certified Robustness to Programmable Transformations in LSTMs

https://t.co/rzZrMXfftp
End-2-End COVID-19 Detection from Breath & Cough Audio

https://t.co/mDdDbyJk5a
Boosting Low-Resource Biomedical QA via Entity-Aware Masking Strategies

https://t.co/mV4Gl4VKMz
Context-Aware Prosody Correction for Text-Based Speech Editing

https://t.co/5ZexKNxtxJ
Modeling the Hallucinating Brain: A Generative Adversarial Framework

https://t.co/JaaqAP8kzp
Differentiating Surgeon Expertise Solely by Eye Movement Features

https://t.co/wdkDOooOEz
End-to-End Automatic Speech Recognition with Deep Mutual Learning

https://t.co/rhcJnk4LSf
Flow-Mixup: Classifying Multi-labeled Medical Images with Corrupted Labels

https://t.co/1mH7eros1q
Large-Context Conversational Representation Learning: Self-Supervised Learning for Conversational Documents

https://t.co/akbrYa9RT9
IronMan: GNN-assisted Design Space Exploration in High-Level Synthesis via Reinforcement Learning

https://t.co/Yw92O9Diix
Making the most of your day: online learning for optimal allocation of time

https://t.co/zaWvxI4IId
Learning the Noise of Failure: Intelligent System Tests for Robots

https://t.co/H8XgGCjcEW
Axial Residual Networks for CycleGAN-based Voice Conversion

https://t.co/pONkkt3VH1
Semi Supervised Learning For Few-shot Audio Classification By Episodic Triplet Mining

https://t.co/PQUEl5yhoL
Exploring Transformers in Natural Language Generation: GPT, BERT, and XLNet

https://t.co/0BUklyDcgQ
Twin Augmented Architectures for Robust Classification of COVID-19 Chest X-Ray Images

https://t.co/ALgZlH3etJ
Machine Learning Based Cyber Attacks Targeting on Controlled Information: A Survey

https://t.co/TdbFrPwsIP
Hierarchical Transformer-based Large-Context End-to-end ASR with Large-Context Knowledge Distillation

https://t.co/GGUpwmvC48
Self-Supervised Features Improve Open-World Learning

https://t.co/Q2xNLyfJW6
A Data Quality-Driven View of MLOps

https://t.co/eQKhvYhUGI
How to Learn when Data Reacts to Your Model: Performative Gradient Descent

https://t.co/QN4iO6kj4b
Learning Student-Friendly Teacher Networks for Knowledge Distillation

https://t.co/DgKFAF1V1V
GradPIM: A Practical Processing-in-DRAM Architecture for Gradient Descent

https://t.co/4NbcthTmEm
Intermediate Layer Optimization for Inverse Problems using Deep Generative Models

https://t.co/lnKWDTeh0B
Intelligent Electric Vehicle Charging Recommendation Based on Multi-Agent Reinforcement Learning

https://t.co/MrbgPYe3h0
Guided Interpolation for Adversarial Training

https://t.co/7k6Hck9ByS
CAP-GAN: Towards Adversarial Robustness with Cycle-consistent Attentional Purification

https://t.co/pZaKRrybX8
Perceptually Constrained Adversarial Attacks

https://t.co/6fQi3Z3PAG
Machine Learning Methods for the Design and Operation of Liquid Rocket Engines -- Research Activities at the DLR Institute of Space Propulsion

https://t.co/g48JL4vPPo
CATE: Computation-aware Neural Architecture Encoding with Transformers

https://t.co/4GANBBXbEB
Doping: A technique for efficient compression of LSTM models using sparse structured additive matrices

https://t.co/AgB279ov90
CrossLight: A Cross-Layer Optimized Silicon Photonic Neural Network Accelerator

https://t.co/KdRZEfjYZZ
Online Apprenticeship Learning

https://t.co/5yFlv6jPQc
Self-Reorganizing and Rejuvenating CNNs for Increasing Model Capacity Utilization

https://t.co/87a52OkRCn
Machine Learning for Mechanical Ventilation Control

https://t.co/fCD6PZsg92
Towards automatic extraction and validation of on-street parking spaces using park-out events data

https://t.co/2s0Gww6xOj
Neural Network Libraries: A Deep Learning Framework Designed from Engineers' Perspectives

https://t.co/twjVSW3DlA
How Convolutional Neural Networks Deal with Aliasing

https://t.co/Xk7kHhbs0l
Detection and severity classification of COVID-19 in CT images using deep learning

https://t.co/zOsH8AKwDT
Cancer Gene Profiling through Unsupervised Discovery

https://t.co/zjkIQLWbB8
Generating 3D structures from a 2D slice with GAN-based dimensionality expansion

https://t.co/sO53SsXarN
Accelerating COVID-19 research with graph mining and transformer-based learning

https://t.co/Rnf0Ny8x2Y
UserReg: A Simple but Strong Model for Rating Prediction

https://t.co/WTWRJe6qFO
Certifiably Robust Variational Autoencoders

https://t.co/yJILKtrZAd
Confidence-Aware Learning Assistant

https://t.co/1HWHeg6I7V
Vehicle to Vehicle (V2V) Communication Protocol: Components, Benefits, Challenges, Safety and Machine Learning Applications

https://t.co/365f93sRgS
Query-by-Example Keyword Spotting system using Multi-head Attention and Softtriple Loss

https://t.co/T8DvRUxwbS
Deep Convolutional and Recurrent Networks for Polyphonic Instrument Classification from Monophonic Raw Audio Waveforms

https://t.co/rsu2GF9Ufo
Saliency-Aware Class-Agnostic Food Image Segmentation

https://t.co/6XwYnXeRfQ
Representing Alzheimer's Disease Progression via Deep Prototype Tree

https://t.co/I7V2BZnkuF
Bi-APC: Bidirectional Autoregressive Predictive Coding for Unsupervised Pre-training and Its Application to Children's ASR

https://t.co/WDiLhG5kre
VIPPrint: A Large Scale Dataset of Printed and Scanned Images for Synthetic Face Images Detection and Source Linking

https://t.co/Qg0tFYzgI4
INSTA-YOLO: Real-Time Instance Segmentation

https://t.co/temd1GTKUg
DeepGLEAM: a hybrid mechanistic and deep learning model for COVID-19 forecasting

https://t.co/18A3HP8zfw
A model for traffic incident prediction using emergency braking data

https://t.co/DbcuGFZSK7
MetaGrad: Adaptation using Multiple Learning Rates in Online Learning

https://t.co/ddE1rzSbR9
Cockpit: A Practical Debugging Tool for Training Deep Neural Networks

https://t.co/m38h270ytx
Neural Architecture Search as Program Transformation Exploration

https://t.co/Xa8husAHix
Universal Adversarial Perturbations Through the Lens of Deep Steganography: Towards A Fourier Perspective

https://t.co/PpGmmXgzRV
Broad-UNet: Multi-scale feature learning for nowcasting tasks

https://t.co/8DiCf40AVw
What does LIME really see in images?

https://t.co/sGAaD331kd
Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction

https://t.co/wBYJuYuW7F
Deep Reinforcement Learning for Backup Strategies against Adversaries

https://t.co/umrehSyR0G
Enhancing into the codec: Noise Robust Speech Coding with Vector-Quantized Autoencoders

https://t.co/2OTRj0jL5x
Bayesian Neural Network Priors Revisited

https://t.co/8CC4eC64bG
Hybrid quantum convolutional neural networks model for COVID-19 prediction using chest X-Ray images

https://t.co/iupCTtwqfo
Comparison of Machine Learning Classifiers to Predict Patient Survival and Genetics of GBM: Towards a Standardized Model for Clinical Implementation

https://t.co/2OUySQbMMF
Mediastinal lymph nodes segmentation using 3D convolutional neural network ensembles and anatomical priors guiding

https://t.co/G4zmOU6gBt
A Non-Intrusive Machine Learning Solution for Malware Detection and Data Theft Classification in Smartphones

https://t.co/36LhXJkfKz
Content-Aware Speaker Embeddings for Speaker Diarisation

https://t.co/4dMtS1Z7Ba
Deep Sound Field Reconstruction in Real Rooms: Introducing the ISOBEL Sound Field Dataset

https://t.co/AqIlgUBtbO
Guided Variational Autoencoder for Speech Enhancement With a Supervised Classifier

https://t.co/M5tX4C1uvO
Annotation Cleaning for the MSR-Video to Text Dataset

https://t.co/cBQcvrZmkv
Data Analytics and Machine Learning Methods, Techniques and Tool for Model-Driven Engineering of Smart IoT Services

https://t.co/dnkaAUxbE6
Bootstrapping Large-Scale Fine-Grained Contextual Advertising Classifier from Wikipedia

https://t.co/PFad4l7j7O
Contrastive Unsupervised Learning for Speech Emotion Recognition

https://t.co/2n55JXA6mS
Personalized Visualization Recommendation

https://t.co/Xo37595w1J
On Automatic Parsing of Log Records

https://t.co/sDoZtEPhMs
Embracing Domain Differences in Fake News: Cross-domain Fake News Detection using Multimodal Data

https://t.co/1Jd7H6bQd0
COVID-19 detection from scarce chest x-ray image data using deep learning

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https://t.co/EWOtKiBQ2s
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https://t.co/6Flz0Uc0Of
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https://t.co/9G4GUwdVmL
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https://t.co/rr2nK3qjZT
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https://t.co/QtCRtssIWS
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https://t.co/SubgUHwjki
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https://t.co/PqJRPMD272
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https://t.co/vpyohaD6pc
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https://t.co/CsxAa7WuYx
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https://t.co/G7PKLUR5t1
Active Face Frontalization using Commodity Unmanned Aerial Vehicles

https://t.co/7QYhzRKtdH
Shape-Tailored Deep Neural Networks

https://t.co/mSP09bcrtw
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https://t.co/OI29qNObFm
Galaxy Zoo DECaLS: Detailed Visual Morphology Measurements from Volunteers and Deep Learning for 314,000 Galaxies

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Learning to Recognize Actions on Objects in Egocentric Video with Attention Dictionaries

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LEAD: LiDAR Extender for Autonomous Driving

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SoFi was founded in 2011 by 4 students who met at Stanford

🎓 The goal was to decrease the student debt burden by giving out lower rates than federal standards

💸 SoFi’s rates ranged from 5.99% to 6.5%, undercutting federal and privates rates which ranged from 6.8% to 16%


By September 2012, SoFi was reported to have commit over $ 200m in loans

📈 This increased to $ 450m by April 2014 and its borrowers reportedly got on average $ 9,400 in savings by refinancing their

💸 Today, SoFi wants to help its customers with every “financial” step of their journey, providing:

· Student loans

· Medical loans

· Home loans

· Renters insurance (powered by $LMND)

· ETFs

· Stocks & cryptos

· Credit card

· Auto insurance (powered by $ROOT)

& more!


⏱ It has also understood that time-pressed and convenience-seeking young professionals value the following elements:

· Speed

· Choice

· Content

· Education

And $SOFI thus turned itself into a convenient, affordable, transparent and user-friendly financial platform


This means that SoFi’s wants to be a “one-stop-shop” for its users

💸 Enabling it to cross-sell its different products and reduce its Customer Acquisition Cost
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Corporate Machiavelli
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@corporatemach
THREAD:

Employees vs Employers

“We who toil for other people have all in some way been captured by pirates and sold into slavery.” –Law 24

It should be said plainly; employment is nothing more than the next step in the evolution of slavery.

The corporation you are employed by has a psychopathic level of indifference as to whether you live or die.

This is not Leftwing political rhetoric; it is a machiavellian reality you will have to contend with.

Your employer is not your ally; they are your adversary.

It is in your best interest for wages to be as high as possible, while it is in your employer’s best interest for wages to be as low as possible.
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Robert Sasu
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@SasuRobert
Thanks to the growing number of people who @getMaiar & engage with the @ElrondNetwork ecosystem, the number of accounts doubled to over 320k & we’re over 2.5M TXs, an unprecedented adoption level for a 6 months-young mainnet.
#hypergrowth100 Day 40
Weekly #elrondtech ⬇️


1/ The Delegation Manager toolset has been released for testnet integrations, ahead of our imminent mainnet upgrade. It enables staking providers to set up & manage staking pools, nodes, fees & other parameters for their

2/ We updated the libp2p libraries to the latest release & found out that they work seamlessly with their old counterparts. Congrats @libp2p team for the effort put in backward compatibility. We know how complex that is.

3/ Redesigned the async call & token transfer syntax in our Arwen WASM VM. Interactions between contracts are now “return types”, which makes execution flow more intuitive. Callbacks have also been

4/ Arwen WASM VM updates continued:
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A Happy Dude
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1/

Thread:

#DishaRavi, one of the founders of "Fridays for future India" has been arrested promptly by Delhi Police.
Let's look at why this was the best move to make.

Also let's see who she is and what her connection is to Greta.

2/

At first glance, you can find that Fridays for Future is an organization founded by Greta Thunberg with branches who conduct school strikes all across the world. Like so.
India, as you can see, is No. 3. And this is the map within India. South seems to dominate. AND


3/

They have global "protests" in almost all countries.
Coming to Disha Ravi, she's an "activist" from "Fridays for Future India" and was featured in Vogue when she joined, providing an educated guess that she may be leading the movement in India. Now...


4/

Let's see what this "climate activist" has done. This is a snippet from Fridays for Future India. As we can see, they have planted weeds all across India. The second SS is a snippet of their "actions" as found on their int'l website. India seems to be one of the highest.


5/

Doesn't end here. This is a snippet from Fridays for future India's instagram page. Take a look at the dates. No need to explain this.
Arresting this woman was the BEST thing that our Police have done till now. They seem to instigate people against GoI, running an agenda.
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Craig Forman
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@cforman
There are so many #HotTakes on the future of news and tech and digital this week. Now nearly half a year distant (and what a year - 2020, ugh!) from CEO and board @mcclatchy, I'd like to add a few thoughts: 1/


As @jbenton said in @NiemanReports : @mcclatchy transformation shows it STILL is possible NOW 'to be operationally profitable while still doing good journalism.' Not easy; Covid made it harder. But POSSIBLE and DONE by the great team in 2020 @mcclatchy. 2/

As @jbenton wrote: the #DIGITALTRANSFORMATION @mcclatchy 'shows a company that has managed the digital transition better than most; at last public count, it was making nearly half its ad revenue in digital and digital subscriptions were up 45% year-over-year.' Such focus 3/

On the future is digital is the SOLE way the still-powerful brands of local news and information will be able to have a business in the inevitable 'printless' future (Not today, not tomorrow, but printless someday) 4/

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The UN just voted to condemn Israel 9 times, and the rest of the world 0.

View the resolutions and voting results here:

The resolution titled "The occupied Syrian Golan," which condemns Israel for "repressive measures" against Syrian citizens in the Golan Heights, was adopted by a vote of 151 - 2 - 14.

Israel and the U.S. voted 'No' https://t.co/HoO7oz0dwr


The resolution titled "Israeli practices affecting the human rights of the Palestinian people..." was adopted by a vote of 153 - 6 - 9.

Australia, Canada, Israel, Marshall Islands, Micronesia, and the U.S. voted 'No' https://t.co/1Ntpi7Vqab


The resolution titled "Israeli settlements in the Occupied Palestinian Territory, including East Jerusalem, and the occupied Syrian Golan" was adopted by a vote of 153 – 5 – 10.

Canada, Israel, Marshall Islands, Micronesia, and the U.S. voted 'No'
https://t.co/REumYgyRuF


The resolution titled "Applicability of the Geneva Convention... to the
Occupied Palestinian Territory..." was adopted by a vote of 154 - 5 - 8.

Canada, Israel, Marshall Islands, Micronesia, and the U.S. voted 'No'
https://t.co/xDAeS9K1kW
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Reshu Nath
Reshu Nath
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'Tera mera rishta kya, hindu, hindu,hindutva' is a clear take on 'tera mera rishta kya,la ilaha illallah'. As much as Hindutva hates the monotheistic religions especially Islam, there's a strange wistfulness and subliminal need at display now, to BE that they hate. 1


Charlie Hebdo doesn’t come up as a cautionary tale now but rather 'why cant we be like that'?
Growing up, Hanuman was an adorable deity for us, who swallowed the sun, or who couldn’t figure out what was Sanjeevani booti so he picked up a whole mountain and came back with it. 2

Or he was loyal, admirable and when he cleaved his chest, you saw both Ram and Sita. Now we have a lot of “Angry Hanuman” stickers. Why is a cute childlike God angry? We don’t know. It's a convenient blank space where to paint all the angst of Hindu Khatre mein hain narrative. 3


The other strange thing that has started happening is pictures of Ram appearing sans Sita. “Jai Siya Ram” has become “Jai Shri Ram”. Some people disingenuously explain it as being the same thing - because Shri is a name of Lakshmi. Not really. Siya is an apbhransh of Sita. 4


Shri is a prefix of respect in this case. Hinduism is being militarised. A woman/Sita has no place in it. Even the militaristic Goddess that is Durga has no place in this conception of neo-Hindu divinity, as evidenced by Dilip Mandal wondering where Durga came from. 5
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Professor
Professor
@DillikiBiili
So friends here is the thread on the recommended pathway for new entrants in the stock market.

Here I will share what I believe are essentials for anybody who is interested in stock markets and the resources to learn them, its from my experience and by no means exhaustive..

First the very basic : The Dow theory, Everybody must have basic understanding of it and must learn to observe High Highs, Higher Lows, Lower Highs and Lowers lows on charts and their

Even those who are more inclined towards fundamental side can also benefit from Dow theory, as it can hint start & end of Bull/Bear runs thereby indication entry and exits.


Next basic is Wyckoff's Theory. It tells how accumulation and distribution happens with regularity and how the market actually

Dow theory is old but
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Raman Shalupau
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Maker movement is doing to startups what startups did to corporations.

Here is why 👇

Startups fixed the problem of innovation, that corporations lack.

In big, slow corporations, innovation is a RISK and distraction from the core $$$ profitable business.

Agile startups could launch, iterate fast and eventually stumble upon new growing market opportunities.

However,

When a startup reaches product-market-fit, it has to 🚀 "grow at all costs" and reach market dominance before some giant corporation can replicate their new product and distribute it to their existing giant customer base.

Startup's "growth at all costs" often means growth at the expense of charging customers $$$ money.

Hence, to be sustainable, startups have to constantly chase investor money.

Startup teams spend more time finding and pleasing investors, than finding and pleasing customers.

95% of startups die because they run out of (investor) money + no business model + crazy investor expectations.

Same way corporations die, when unable to adjust to new technology and market shifts.
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Anshul Pandey
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@Anshulspiritual
BRAHMA VAIVARTA PURAN: IMPORTANCE AND CHARACTERISTICS.

This Puran introduces us to way of Vedas. On the request of Narad Muni Bhagwan Saavarni had preached this Puran. It is a summary of Dharma, Arth, Moksha etc.


Listening to this Puran one gets automatically attached to Vishnu and Shiva and realize that there is no difference between them. Vyasji divided this book into four parts. It has eighteen thousand shlokas. This whole book is in the form of dialogue between Suutji and Maharishi's.

The first part Brahmkhand, consists of Shrishti description. Here Shri is known as Para Brahma and description of Gokul is also mentioned, It also narrates the argument between Brahma and Narad in which both were defeated, and then Narad went to Shiva to attain more gyan.

Shivji advised him to go to Bhagwan Saavarni for this. Narad goes to Saavarni ashram to seek Knowledge and is totally amazed by the sorroundings.

Next is Prakriti khand which consists of dialogue between Narad and Saavarni where they discuss the

Importance of Shri Krishna through various stories. Then there is the discussion of Prakriti and its various hues. Listening to this gets you wealth.
Next is Ganesh Khand which describes the Punyak vrat done by Parvati ji. After this it narrates the birth of Kartikeya and Ganesh.
RELIGION