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Showing below up to 210 results in range #1 to #210.
- "Why Should I Trust You?": Explaining the Predictions of Any Classifier
- ALBERT
- ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
- A Bayesian Perspective on Generalization and Stochastic Gradient Descent
- A Game Theoretic Approach to Class-wise Selective Rationalization
- A Knowledge-Grounded Neural Conversation Model
- A Neural Representation of Sketch Drawings
- A universal SNP and small-indel variant caller using deep neural networks
- Adacompress: Adaptive compression for online computer vision services
- Adversarial Fisher Vectors for Unsupervised Representation Learning
- Annotating Object Instances with a Polygon RNN
- Another look at distance-weighted discrimination
- Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin
- Augmix: New Data Augmentation method to increase the robustness of the algorithm
- Automatic Bank Fraud Detection Using Support Vector Machines
- Bag of Tricks for Efficient Text Classification
- Batch Normalization
- Batch Normalization Summary
- Being Bayesian about Categorical Probability
- Breaking Certified Defenses: Semantic Adversarial Examples With Spoofed Robustness Certificates
- Breaking the Softmax Bottleneck: A High-Rank RNN Language Model
- Bsodjahi
- CRITICAL ANALYSIS OF SELF-SUPERVISION
- CapsuleNets
- CatBoost: unbiased boosting with categorical features
- Co-Teaching
- Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments
- Convolutional Neural Networks for Sentence Classification
- Convolutional Sequence to Sequence Learning
- Convolutional neural network for diagnosis of viral pneumonia and COVID-19 alike diseases
- Countering Adversarial Images Using Input Transformations
- Curiosity-driven Exploration by Self-supervised Prediction
- DCN plus: Mixed Objective And Deep Residual Coattention for Question Answering
- DON'T DECAY THE LEARNING RATE , INCREASE THE BATCH SIZE
- DREAM TO CONTROL: LEARNING BEHAVIORS BY LATENT IMAGINATION
- DeepVO Towards end to end visual odometry with deep RNN
- Deep Alternative Neural Network: Exploring Contexts As Early As Possible For Action Recognition
- Deep Double Descent Where Bigger Models and More Data Hurt
- Deep Learning for Cardiologist-level Myocardial Infarction Detection in Electrocardiograms
- Deep Learning for Extreme Multi-label Text Classification
- Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling
- Deep Residual Learning for Image Recognition
- Deep Residual Learning for Image Recognition Summary
- Deep Transfer Learning with Joint Adaptation Networks
- Dense Passage Retrieval for Open-Domain Question Answering
- Depthwise Convolution Is All You Need for Learning Multiple Visual Domains
- Describtion of Text Mining
- Do Deep Neural Networks Suffer from Crowding
- Do Vision Transformers See Like CNN
- Don't Just Blame Over-parametrization
- Don't Just Blame Over-parametrization Summary
- Dynamic Routing Between Capsules
- Dynamic Routing Between Capsules STAT946
- Dynamic Routing Between Capsulesl
- End-to-End Differentiable Adversarial Imitation Learning
- End to end Active Object Tracking via Reinforcement Learning
- Evaluating Machine Accuracy on ImageNet
- Extreme Multi-label Text Classification
- Fairness Without Demographics in Repeated Loss Minimization
- FeUdal Networks for Hierarchical Reinforcement Learning
- Fix your classifier: the marginal value of training the last weight layer
- From Variational to Deterministic Autoencoders
- Functional regularisation for continual learning with gaussian processes
- Generating Image Descriptions
- Going Deeper with Convolutions
- GradientLess Descent
- Gradient Episodic Memory for Continual Learning
- Graph Structure of Neural Networks
- Hash Embeddings for Efficient Word Representations
- Hierarchical Question-Image Co-Attention for Visual Question Answering
- IPBoost
- Imagination-Augmented Agents for Deep Reinforcement Learning
- Imagination Augmented Agents for Deep Reinforcement Learning
- Improving neural networks by preventing co-adaption of feature detectors
- Improving neural networks by preventing co-adaption of feature detectors 2020 Fall
- Incremental Boosting Convolutional Neural Network for Facial Action Unit Recognition
- Influenza Forecasting Framework based on Gaussian Processes
- Influenza Forecasting Framework based on Gaussian processes Summary
- Label-Free Supervision of Neural Networks with Physics and Domain Knowledge
- Learning Combinatorial Optimzation
- Learning The Difference That Makes A Difference With Counterfactually-Augmented Data
- Learning to Navigate in Cities Without a Map
- Learning to Teach
- Loss Function Search for Face Recognition
- MULTI-VIEW DATA GENERATION WITHOUT VIEW SUPERVISION
- Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction
- MarrNet: 3D Shape Reconstruction via 2.5D Sketches
- Mask RCNN
- Memory-Based Parameter Adaptation
- Meta-Learning-For-Domain Generalization
- Meta-Learning For Domain Generalization
- ModelFramework.jpg
- Model Agnostic Learning of Semantic Features
- Multi-scale Dense Networks for Resource Efficient Image Classification
- Music Recommender System Based using CRNN
- Neural Audio Synthesis of Musical Notes with WaveNet autoencoders
- Neural ODEs
- Obfuscated Gradients Give a False Sense of Security Circumventing Defenses to Adversarial Examples
- On The Convergence Of ADAM And Beyond
- One-Shot Imitation Learning
- One-Shot Object Detection with Co-Attention and Co-Excitation
- One pixel attack for fooling deep neural networks
- Patch Based Convolutional Neural Network for Whole Slide Tissue Image Classification
- Physics-informed neural networks: A deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
- Pixels to Graphs by Associative Embedding
- Point-of-Interest Recommendation: Exploiting Self-Attentive Autoencoders with Neighbor-Aware Influence
- PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Space
- Poison Frogs Neural Networks
- Pre-Training-Tasks-For-Embedding-Based-Large-Scale-Retrieval
- Pre-Training Tasks For Embedding-Based Large-Scale Retrieval
- Predicting Floor Level For 911 Calls with Neural Network and Smartphone Sensor Data
- Predicting Hurricane Trajectories Using a Recurrent Neural Network
- Reinforcement Learning of Theorem Proving
- Representations of Words and Phrases and their Compositionality
- Research Papers Classification System
- Research on Multiple Classification Based on Improved SVM Algorithm for Balanced Binary Decision Tree
- Roberta
- Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias
- Robust Imitation Learning from Noisy Demonstrations
- Robust Imitation of Diverse Behaviors
- Robust Probabilistic Modeling with Bayesian Data Reweighting
- STAT946F17/Cognitive Psychology For Deep Neural Networks: A Shape Bias Case Study
- STAT946F17/Decoding with Value Networks for Neural Machine Translation
- STAT946F17/ Automated Curriculum Learning for Neural Networks
- STAT946F17/ Coupled GAN
- STAT946F17/ Dance Dance Convolution
- STAT946F17/ Improved Variational Inference with Inverse Autoregressive Flow
- STAT946F17/ Learning Important Features Through Propagating Activation Differences
- STAT946F17/ Learning a Probabilistic Latent Space of Object Shapes via 3D GAN
- STAT946F17/ Teaching Machines to Describe Images via Natural Language Feedback
- Searching For Efficient Multi Scale Architectures For Dense Image Prediction
- Self-Supervised Learning of Pretext-Invariant Representations
- Semantic Relation Classification——via Convolution Neural Network
- ShakeDrop Regularization
- Speech2Face: Learning the Face Behind a Voice
- Spherical CNNs
- Streaming Bayesian Inference for Crowdsourced Classification
- Summary - A Neural Representation of Sketch Drawings
- Summary of A Probabilistic Approach to Neural Network Pruning
- SuperGLUE
- Superhuman AI for Multiplayer Poker
- Surround Vehicle Motion Prediction
- Synthesizing Programs for Images usingReinforced Adversarial Learning
- THE LOGICAL EXPRESSIVENESS OF GRAPH NEURAL NETWORKS
- Task Understanding from Confushing Multitask Data
- Task Understanding from Confusing Multi-task Data
- The Curious Case of Degeneration
- The Detection of Black Ice Accidents Using CNNs
- This Looks Like That: Deep Learning for Interpretable Image Recognition
- Time-series Generative Adversarial Networks
- Towards Deep Learning Models Resistant to Adversarial Attacks
- Traffic Sign Recognition System (TSRS): SVM and Convolutional Neural Network
- Training And Inference with Integers in Deep Neural Networks
- U-Time:A Fully Convolutional Network for Time Series Segmentation Applied to Sleep Staging Summary
- Understanding Image Motion with Group Representations
- Universal Style Transfer via Feature Transforms
- Unsupervised Learning of Optical Flow via Brightness Constancy and Motion Smoothness
- Unsupervised Machine Translation Using Monolingual Corpora Only
- Unsupervised Neural Machine Translation
- Visual Reinforcement Learning with Imagined Goals
- Wasserstein Auto-Encoders
- Wasserstein Auto-encoders
- Wavelet Pooling CNN
- When Does Self-Supervision Improve Few-Shot Learning?
- When can Multi-Site Datasets be Pooled for Regression? Hypothesis Tests, l2-consistency and Neuroscience Applications: Summary
- Wide and Deep Learning for Recommender Systems
- Word translation without parallel data
- XGBoost
- XGBoost: A Scalable Tree Boosting System
- Zero-Shot Visual Imitation
- a fair comparison of graph neural networks for graph classification
- a neural representation of sketch drawings
- conditional neural process
- learn what not to learn
- meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting
- orthogonal gradient descent for continual learning
- policy optimization with demonstrations
- stat441F18/TCNLM
- stat441F18/YOLO
- stat441w18/A New Method of Region Embedding for Text Classification
- stat441w18/Convolutional Neural Networks for Sentence Classification
- stat441w18/Image Question Answering using CNN with Dynamic Parameter Prediction
- stat441w18/Saliency-based Sequential Image Attention with Multiset Prediction
- stat441w18/e-gan
- stat441w18/mastering-chess-and-shogi-self-play
- stat441w18/summary 1
- stat841F18/
- stat946F18/Autoregressive Convolutional Neural Networks for Asynchronous Time Series
- stat946F18/Beyond Word Importance Contextual Decomposition to Extract Interactions from LSTMs
- stat946F18/differentiableplasticity
- stat946F20/GradientLess Descent
- stat946w18/
- stat946w18/AmbientGAN: Generative Models from Lossy Measurements
- stat946w18/Hierarchical Representations for Efficient Architecture Search
- stat946w18/IMPROVING GANS USING OPTIMAL TRANSPORT
- stat946w18/Implicit Causal Models for Genome-wide Association Studies
- stat946w18/MaskRNN: Instance Level Video Object Segmentation
- stat946w18/Predicting Floor-Level for 911 Calls with Neural Networks and Smartphone Sensor Data
- stat946w18/Rethinking the Smaller-Norm-Less-Informative Assumption in Channel Pruning of Convolutional Layers
- stat946w18/Self Normalizing Neural Networks
- stat946w18/Spectral
- stat946w18/Spectral normalization for generative adversial network
- stat946w18/Synthetic and natural noise both break neural machine translation
- stat946w18/Tensorized LSTMs
- stat946w18/Towards Image Understanding From Deep Compression Without Decoding
- stat946w18/Unsupervised Machine Translation Using Monolingual Corpora Only
- stat946w18/Wavelet Pooling For Convolutional Neural Networks
- test
- time-series-using-GAN
- what game are we playing