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- ALBERT
- ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
- A Bayesian Perspective on Generalization and Stochastic Gradient Descent
- A Brief Survey of Text Mining: Classification, Clustering and Extraction Techniques
- 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 Attacks on Copyright Detection Systems
- Adversarial Fisher Vectors for Unsupervised Representation Learning
- Annotating Object Instances with a Polygon RNN
- Another look at distance-weighted discrimination
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- 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
- BERTScore: Evaluating Text Generation with BERT
- Bag of Tricks for Efficient Text Classification
- Batch Normalization
- Batch Normalization Summary
- Bayesian Network as a Decision Tool for Predicting ALS Disease
- 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
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- CatBoost: unbiased boosting with categorical features
- Co-Teaching
- Conditional Image Synthesis with Auxiliary Classifier GANs
- 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
- DETECTING STATISTICAL INTERACTIONS FROM NEURAL NETWORK WEIGHTS
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- 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 Exploration via Bootstrapped DQN
- 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
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- 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
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- Dialog-based Language Learning
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- Dynamic Routing Between Capsules
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- Efficient kNN Classification with Different Numbers of Nearest Neighbors
- End-to-End Differentiable Adversarial Imitation Learning
- End to end Active Object Tracking via Reinforcement Learning
- Evaluating Machine Accuracy on ImageNet
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- Extreme Multi-label Text Classification
- F18-STAT841-Proposal
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- Fairness Without Demographics in Repeated Loss Minimization
- FeUdal Networks for Hierarchical Reinforcement Learning
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- Fix your classifier: the marginal value of training the last weight layer
- From Variational to Deterministic Autoencoders
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- Generating Image Descriptions
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- Imagination-Augmented Agents for Deep Reinforcement Learning
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- Incremental Boosting Convolutional Neural Network for Facial Action Unit Recognition
- Influenza Forecasting Framework based on Gaussian Processes
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- Learning to Navigate in Cities Without a Map
- Learning to Teach
- LightRNN: Memory and Computation-Efficient Recurrent Neural Networks
- 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
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- Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
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- Model Agnostic Learning of Semantic Features
- Modular Multitask Reinforcement Learning with Policy Sketches
- Multi-scale Dense Networks for Resource Efficient Image Classification
- Music Recommender System Based using CRNN
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- Neural Audio Synthesis of Musical Notes with WaveNet autoencoders
- Neural ODEs
- Neural Speed Reading via Skim-RNN
- 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
- Proposal for STAT946 (Deep Learning) final projects Fall 2017
- 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
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- 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/Conditional Image Generation with PixelCNN Decoders
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- STAT946F17/ Automated Curriculum Learning for Neural Networks
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- STAT946F17/ Dance Dance Convolution
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- STAT946F17/ Learning a Probabilistic Latent Space of Object Shapes via 3D GAN
- STAT946F17/ Teaching Machines to Describe Images via Natural Language Feedback
- STAT946F20/BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
- Searching For Efficient Multi Scale Architectures For Dense Image Prediction
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- 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 for survey of neural networked-based cancer prediction models from microarray data
- 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
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- 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
- Understanding the Effective Receptive Field in Deep Convolutional Neural Networks
- Universal Style Transfer via Feature Transforms
- Unsupervised Domain Adaptation with Residual Transfer Networks
- 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
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- 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
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- Wide and Deep Learning for Recommender Systems
- Word translation without parallel data
- XGBoost
- XGBoost: A Scalable Tree Boosting System
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- a Deeper Look into Importance Sampling
- a Direct Formulation For Sparse PCA Using Semidefinite Programming
- a Dynamic Bayesian Network Click Model for Web Search Ranking
- a Dynamic Bayesian Network Click Model for web search ranking
- a New Approach to Collaborative Filtering: Operator Estimation with Spectral Regularization
- a Penalized Matrix Decomposition, with Applications to Sparse Principal Components and Canonical Correlation Analysis
- a Rank Minimization Heuristic with Application to Minimum Order System Approximation
- a fair comparison of graph neural networks for graph classification
- a fast learning algorithm for deep belief nets
- a neural representation of sketch drawings
- acceptance-Rejection Sampling
- adaptive dimension reduction for clustering high dimensional data
- again on Markov Chain
- an HDP-HMM for Systems with State Persistence
- bayesian and Frequentist Schools of Thought
- binomial Probability Monte Carlo Sampling June 2 2009
- cardinality Restricted Boltzmann Machines
- compressed Sensing Reconstruction via Belief Propagation
- compressive Sensing
- compressive Sensing (Candes)
- conditional neural process
- consistency of Trace Norm Minimization
- context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis
- continuous space language models
- contributions on Context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis
- contributions on Quantifying Cancer Progression with Conjunctive Bayesian Networks
- contributions on Video-Based Face Recognition Using Adaptive Hidden Markov Models
- convex and Semi Nonnegative Matrix Factorization
- copyofstat341
- decentralised Data Fusion: A Graphical Model Approach (Summary)
- deepGenerativeModels
- deep Convolutional Neural Networks For LVCSR
- deep Generative Stochastic Networks Trainable by Backprop
- deep Learning of the tissue-regulated splicing code
- deep Neural Nets as a Method for Quantitative Structure–Activity Relationships
- deep Sparse Rectifier Neural Networks
- deep neural networks for acoustic modeling in speech recognition
- deflation Method for Penalized Matrix Decomposition Sparse PCA
- deflation Methods for Sparse PCA
- dimensionality Reduction for Supervised Learning with Reproducing Kernel Hilbert Spaces
- discLDA: Discriminative Learning for Dimensionality Reduction and Classification
- distributed Representations of Words and Phrases and their Compositionality
- dropout
- extracting and Composing Robust Features with Denoising Autoencoders
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- from Machine Learning to Machine Reasoning
- generating Random Numbers
- generating text with recurrent neural networks
- genetics
- goingDeeperWithConvolutions
- graph Laplacian Regularization for Larg-Scale Semidefinite Programming
- graphical models for structured classification, with an application to interpreting images of protein subcellular location patterns
- graves et al., Speech recognition with deep recurrent neural networks
- hamming Distance Metric Learning
- hierarchical Dirichlet Processes
- human-level control through deep reinforcement learning
- imageNet Classification with Deep Convolutional Neural Networks
- importance Sampling June 2 2009
- importance Sampling and Markov Chain Monte Carlo (MCMC)
- importance Sampling and Monte Carlo Simulation
- incremental Learning, Clustering and Hierarchy Formation of Whole Body Motion Patterns using Adaptive Hidden Markov Chains(Summary)
- independent Component Analysis: algorithms and applications
- inductive Kernel Low-rank Decomposition with Priors: A Generalized Nystrom Method
- infoboxtest
- is Multinomial PCA Multi-faceted Clustering or Dimensionality Reduction
- joint training of a convolutional network and a graphical model for human pose estimation
- kernel Dimension Reduction in Regression
- kernel Spectral Clustering for Community Detection in Complex Networks
- kernelized Locality-Sensitive Hashing
- kernelized Sorting
- large-Scale Supervised Sparse Principal Component Analysis