Thread by @stephenwithavee

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?!

Analyzing the Machine Learning Conference Review Process

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torchdistill: A Modular, Configuration-Driven Framework for Knowledge Distillation

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TLeague: A Framework for Competitive Self-Play based Distributed Multi-Agent Reinforcement Learning

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Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting with their Explanations

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Attention-Based Learning on Molecular Ensembles

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Regret-optimal measurement-feedback control

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Prediction of neonatal mortality in Sub-Saharan African countries using data-level linkage of multiple surveys

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Batch Normalization Embeddings for Deep Domain Generalization

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Temporal Autoencoder with U-Net Style Skip-Connections for Frame Prediction

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Energy Forecasting in Smart Grid Systems: A Review of the State-of-the-art Techniques

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Energy Forecasting in Smart Grid Systems: A Review of the State-of-the-art Techniques

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Enhanced Scene Specificity with Sparse Dynamic Value Estimation

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Causal inference using deep neural networks

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Interpretable Models in ANNs

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C-Learning: Horizon-Aware Cumulative Accessibility Estimation

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FireSRnet: Geoscience-Driven Super-Resolution of Future Fire Risk from Climate Change

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Hindsight Network Credit Assignment

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Improving Clinical Outcome Predictions Using Convolution overMedical Entities with Multimodal Learning

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Trust but Verify: Assigning Prediction Credibility by Counterfactual Constrained Learning

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Open-World Learning Without Labels

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Generalized Variational Continual Learning

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All You Need is a Good Functional Prior for Bayesian Deep Learning

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Interpreting U-Nets via Task-Driven Multiscale Dictionary Learning

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StyleSpace Analysis: Disentangled Controls for StyleGAN Image Generation

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AI virtues -- The missing link in putting AI ethics into practice

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Symmetry-Aware Actor-Critic for 3D Molecular Design

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Simple statistical methods for unsupervised brain anomaly detection on MRI are competitive to deep learning methods

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Bootstrap an end-to-end ASR system by multilingual training, transfer learning, text-to-text mapping and synthetic audio

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Denmark's Participation in the Search Engine TREC COVID-19 Challenge: Lessons Learned about Searching for Precise Biomedical Scientific Information on COVID-19

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The Unreasonable Effectiveness of Encoder-Decoder Networks for Retinal Vessel Segmentation

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Automatic Identification of MHD Modes in Magnetic Fluctuations Spectrograms using Deep Learning Techniques

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Combining Semantic Guidance and Deep Reinforcement Learning For Generating Human Level Paintings

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CellSegmenter: unsupervised representation learning and instance segmentation of modular images

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Minimax Estimation of Distances on a Surface and Minimax Manifold Learning in the Isometric-to-Convex Setting

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Experiments on transfer learning architectures for biomedical relation extraction

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Play Fair: Frame Attributions in Video Models

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The Application of Data Mining in the Production Processes

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Classification supporting COVID-19 diagnostics based on patient survey data

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Generative Adversarial Stacked Autoencoders

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Making Graph Neural Networks Worth It for Low-Data Molecular Machine Learning

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xFraud: Explainable Fraud Transaction Detection on Heterogeneous Graphs

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Lipophilicity Prediction with Multitask Learning and Molecular Substructures Representation

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AI Discovering a Coordinate System of Chemical Elements: Dual Representation by Variational Autoencoders

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Adam$^+$: A Stochastic Method with Adaptive Variance Reduction

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Provably-Robust Runtime Monitoring of Neuron Activation Patterns

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On the Adversarial Robustness of 3D Point Cloud Classification

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Learning Principle of Least Action with Reinforcement Learning

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Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder

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Solving The Lunar Lander Problem under Uncertainty using Reinforcement Learning

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RTFN: A Robust Temporal Feature Network for Time Series Classification

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REPAINT: Knowledge Transfer in Deep Actor-Critic Reinforcement Learning

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Remaining Useful Life Estimation Under Uncertainty with Causal GraphNets

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A Use of Even Activation Functions in Neural Networks

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MicroNet: Towards Image Recognition with Extremely Low FLOPs

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Explainable Multivariate Time Series Classification: A Deep Neural Network Which Learns To Attend To Important Variables As Well As Informative Time Intervals

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Multi-Stage CNN-Based Monocular 3D Vehicle Localization and Orientation Estimation

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Tight Integrated End-to-End Training for Cascaded Speech Translation

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Two-Way Neural Machine Translation: A Proof of Concept for Bidirectional Translation Modeling using a Two-Dimensional Grid

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SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration

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Fetal ECG Extraction from Maternal ECG using attention-based Asymmetric CycleGAN

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Deep learning for video game genre classification

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Self-Supervised Transformers for Activity Classification using Ambient Sensors

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A Reusable Framework Based on Reinforcement Learning to Design Antennas for Curved Surfaces

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A Generalizable Model for Fault Detection in Offshore Wind Turbines Based on Deep Learning

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Self-supervised transfer learning of physiological representations from free-living wearable data

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EEG-GCNN: Augmenting Electroencephalogram-based Neurological Disease Diagnosis using a Domain-guided Graph Convolutional Neural Network

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Adversarial Generation of Continuous Images

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Synth2Aug: Cross-domain speaker recognition with TTS synthesized speech

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Machine Learning enables Ultra-Compact Integrated Photonics through Silicon-Nanopattern Digital Metamaterials

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Accurate and Rapid Diagnosis of COVID-19 Pneumonia with Batch Effect Removal of Chest CT-Scans and Interpretable Artificial Intelligence

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Detecting hidden signs of diabetes in external eye photographs

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From Pixels to Legs: Hierarchical Learning of Quadruped Locomotion

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Improving epidemic testing and containment strategies using machine learning

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Multi-task Language Modeling for Improving Speech Recognition of Rare Words

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Nudge Attacks on Point-Cloud DNNs

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Logarithmic Regret for Reinforcement Learning with Linear Function Approximation

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Exploring Contrastive Learning in Human Activity Recognition for Healthcare

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condLSTM-Q: A novel deep learning model for predicting Covid-19 mortality in fine geographical Scale

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Exploring Alternatives to Softmax Function

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Social Determinants of Recidivism: A Machine Learning Solution

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Generative Adversarial Simulator

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Time Series Data Imputation: A Survey on Deep Learning Approaches

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AutoGraph: Automated Graph Neural Network

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IC Neuron: An Efficient Unit to Construct Neural Networks

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Detection and Classification of mental illnesses on social media using RoBERTa

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Learning a Deep Generative Model like a Program: the Free Category Prior

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A Population-based Hybrid Approach to Hyperparameter Optimization for Neural Networks

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Distributed Deep Reinforcement Learning: An Overview

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AST-GCN: Attribute-Augmented Spatiotemporal Graph Convolutional Network for Traffic Forecasting

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Time series classification for predictive maintenance on event logs

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On the Convergence of Reinforcement Learning

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Neural Group Testing to Accelerate Deep Learning

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Self-adapting Robustness in Demand Learning

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SHOT-VAE: Semi-supervised Deep Generative Models With Label-aware ELBO Approximations

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Very Deep VAEs Generalize Autoregressive Models and Can Outperform Them on Images

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Learn to Bind and Grow Neural Structures

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Transfer Learning for Oral Cancer Detection using Microscopic Images

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High Fidelity Interactive Video Segmentation Using Tensor Decomposition Boundary Loss Convolutional Tessellations and Context Aware Skip Connections

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Yet it moves: Learning from Generic Motions to Generate IMU data from YouTube videos

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Automatic Detection and Classification of Tick-borne Skin Lesions using Deep Learning

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Automated Quality Assessment of Hand Washing Using Deep Learning

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Peeking inside the Black Box: Interpreting Deep Learning Models for Exoplanet Atmospheric Retrievals

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Sparse generative modeling of protein-sequence families

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Application of Facial Recognition using Convolutional Neural Networks for Entry Access Control

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Differentiable Computational Geometry for 2D and 3D machine learning

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Deep Learning in EEG: Advance of the Last Ten-Year Critical Period

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Data Mining Techniques in Predicting Breast Cancer

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FP-NAS: Fast Probabilistic Neural Architecture Search

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Third ArchEdge Workshop: Exploring the Design Space of Efficient Deep Neural Networks

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Visual Recognition of Great Ape Behaviours in the Wild

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Learning-based attacks in Cyber-Physical Systems: Exploration, Detection, and Control Cost trade-offs

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CancerNet-SCa: Tailored Deep Neural Network Designs for Detection of Skin Cancer from Dermoscopy Images

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Open-Vocabulary Object Detection Using Captions

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Teaching Key Machine Learning Principles Using Anti-learning Datasets

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Upgraded W-Net with Attention Gates and its Application in Unsupervised 3D Liver Segmentation

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Self-Supervised learning with cross-modal transformers for emotion recognition

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Deep learning insights into cosmological structure formation

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Design of Experiments for Verifying Biomolecular Networks

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Synthetic Image Rendering Solves Annotation Problem in Deep Learning Nanoparticle Segmentation

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Empirical Evaluation of Deep Learning Model Compression Techniques on the WaveNet Vocoder

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PSD2 Explainable AI Model for Credit Scoring

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Finding Prerequisite Relations between Concepts using Textbook

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StressNet: Deep Learning to Predict Stress With Fracture Propagation in Brittle Materials

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A global universality of two-layer neural networks with ReLU activations

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Complexity Controlled Generative Adversarial Networks

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Long Short Term Memory Networks for Bandwidth Forecasting in Mobile Broadband Networks under Mobility

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COVID-19 and Mental Health/Substance Use Disorders on Reddit: A Longitudinal Study

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Detection of COVID-19 Using Heart Rate and Blood Pressure: Lessons Learned from Patients with ARDS

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User and Item-aware Estimation of Review Helpfulness

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Towards Abstract Relational Learning in Human Robot Interaction

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Assessing out-of-domain generalization for robust building damage detection

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Collaborative Storytelling with Large-scale Neural Language Models

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A Survey on Deep Learning Based Point-Of-Interest (POI) Recommendations

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Robot Gaining Accurate Pouring Skills through Self-Supervised Learning and Generalization

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FlowStep3D: Model Unrolling for Self-Supervised Scene Flow Estimation

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NeVer 2.0: Learning, Verification and Repair of Deep Neural Networks

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Using Text to Teach Image Retrieval

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Effective, Efficient and Robust Neural Architecture Search

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A Temporal Convolution Network Approach to State-of-Charge Estimation in Li-ion Batteries

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SOCAIRE: Forecasting and Monitoring Urban Air Quality in Madrid

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Node Similarity Preserving Graph Convolutional Networks

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High-Throughput Approach to Modeling Healthcare Costs Using Electronic Healthcare Records

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Persuasive Dialogue Understanding: the Baselines and Negative Results

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Everybody Sign Now: Translating Spoken Language to Photo Realistic Sign Language Video

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Lifelong Knowledge Learning in Rule-based Dialogue Systems

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Novel Classification of Ischemic Heart Disease Using Artificial Neural Network

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Universal MelGAN: A Robust Neural Vocoder for High-Fidelity Waveform Generation in Multiple Domains

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Multi-stage Speaker Extraction with Utterance and Frame-Level Reference Signals

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FinRL: A Deep Reinforcement Learning Library for Automated Stock Trading in Quantitative Finance

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European Strategy on AI: Are we truly fostering social good?

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The Human Effect Requires Affect: Addressing Social-Psychological Factors of Climate Change with Machine Learning

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Multimodal Learning for Hateful Memes Detection

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RRCN: A Reinforced Random Convolutional Network based Reciprocal Recommendation Approach for Online Dating

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SAR-Net: A End-to-End Deep Speech Accent Recognition Network

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OrgMining 2.0: A Novel Framework for Organizational Model Mining from Event Logs

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CLAWS: Clustering Assisted Weakly Supervised Learning with Normalcy Suppression for Anomalous Event Detection

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Semi-supervised Gated Recurrent Neural Networks for Robotic Terrain Classification

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Elementary Effects Analysis of factors controlling COVID-19 infections in computational simulation reveals the importance of Social Distancing and Mask Usage

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FakeSafe: Human Level Data Protection by Disinformation Mapping using Cycle-consistent Adversarial Network

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Spatially Correlated Patterns in Adversarial Images

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Explainable Composition of Aggregated Assistants

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AI Governance for Businesses

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Reachable Polyhedral Marching (RPM): A Safety Verification Algorithm for Robotic Systems with Deep Neural Network Components

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OAK: Ontology-Based Knowledge Map Model for Digital Agriculture

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The Dynamic of Body and Brain Co-Evolution

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Investigating Emotion-Color Association in Deep Neural Networks

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Video SemNet: Memory-Augmented Video Semantic Network

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SophiaPop: Experiments in Human-AI Collaboration on Popular Music

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Learning Synthetic to Real Transfer for Localization and Navigational Tasks

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Electric Vehicle Charging Infrastructure Planning: A Scalable Computational Framework

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Creative Sketch Generation

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Active Inference and Behavior Trees for Reactive Action Planning and Execution in Robotics

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Exploring Text Specific and Blackbox Fairness Algorithms in Multimodal Clinical NLP

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Bidirectional RNN-based Few Shot Learning for 3D Medical Image Segmentation

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A Sequence-to-Sequence Approach to Dialogue State Tracking

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