# All pages

- "Why Should I Trust You?": Explaining the Predictions of Any Classifier
- 13Stat946papers
- 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 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 Knowledge-Grounded Neural Conversation Model
- A Neural Representation of Sketch Drawings
- 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 fast learning algorithm for deep belief nets
- A universal SNP and small-indel variant caller using deep neural networks
- Acceptance-Rejection Sampling
- Adacompress: Adaptive compression for online computer vision services
- Adaptive dimension reduction for clustering high dimensional data
- Adversarial Attacks on Copyright Detection Systems
- Adversarial Fisher Vectors for Unsupervised Representation Learning
- Again on Markov Chain
- AmbientGAN: Generative Models from Lossy Measurements
- An HDP-HMM for Systems with State Persistence
- Annotating Object Instances with a Polygon RNN
- Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin
- Augmix: New Data Augmentation method to increase the robustness of the algorithm
- BERTScore: Evaluating Text Generation with BERT
- Bag of Tricks for Efficient Text Classification
- Batch Normalization
- Batch Normalization Summary
- Bayesian and Frequentist Schools of Thought
- Being Bayesian about Categorical Probability
- Binomial Probability Monte Carlo Sampling June 2 2009
- Breaking Certified Defenses: Semantic Adversarial Examples With Spoofed Robustness Certificates
- Breaking the Softmax Bottleneck: A High-Rank RNN Language Model
- CRITICAL ANALYSIS OF SELF-SUPERVISION
- CapsuleNets
- Cardinality Restricted Boltzmann Machines
- Cm361
- Co-Teaching
- Compressed Sensing Reconstruction via Belief Propagation
- Compressive Sensing
- Compressive Sensing (Candes)
- Conditional Image Synthesis with Auxiliary Classifier GANs
- Consistency of Trace Norm Minimization
- Context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis
- Continuous Adaptation via Meta-Learning in Nonstationary and Competitive Environments
- 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
- Convolutional Neural Networks for Sentence Classiﬁcation
- Convolutional Sequence to Sequence Learning
- Copyofstat341
- 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
- DON'T DECAY THE LEARNING RATE , INCREASE THE BATCH SIZE
- DREAM TO CONTROL: LEARNING BEHAVIORS BY LATENT IMAGINATION
- Decentralised Data Fusion: A Graphical Model Approach (Summary)
- DeepGenerativeModels
- DeepVO Towards end to end visual odometry with deep RNN
- Deep Alternative Neural Network: Exploring Contexts As Early As Possible For Action Recognition
- Deep Convolutional Neural Networks For LVCSR
- Deep Exploration via Bootstrapped DQN
- Deep Generative Stochastic Networks Trainable by Backprop
- Deep Learning for Cardiologist-level Myocardial Infarction Detection in Electrocardiograms
- Deep Learning of the tissue-regulated splicing code
- Deep Neural Nets as a Method for Quantitative Structure–Activity Relationships
- Deep Reinforcement Learning in Continuous Action Spaces a Case Study in the Game of Simulated Curling
- Deep Residual Learning for Image Recognition
- Deep Sparse Rectifier Neural Networks
- Deep Transfer Learning with Joint Adaptation Networks
- Deep neural networks for acoustic modeling in speech recognition
- Deflation Method for Penalized Matrix Decomposition Sparse PCA
- Deflation Methods for Sparse PCA
- Dense Passage Retrieval for Open-Domain Question Answering
- Describtion of Text Mining
- Dialog-based Language Learning
- 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
- Do Deep Neural Networks Suffer from Crowding
- Dropout
- Dynamic Routing Between Capsules
- Dynamic Routing Between Capsules STAT946
- Dynamic Routing Between Capsulesl
- 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
- Extracting and Composing Robust Features with Denoising Autoencoders
- Extreme Multi-label Text Classification
- F10 Stat841 digest
- F11Stat841EditorSignUp
- F11Stat841presentation
- F11Stat841proposal
- F11Stat946ass
- F11Stat946papers
- F11Stat946presentation
- F11stat946EditorSignUp
- F14Stat842EditorSignUp
- F15Stat946PaperSignUp
- F18-STAT841-Proposal
- F18-STAT946-Proposal
- F20-STAT 441/841 CM 763-Proposal
- F20-STAT 946-Proposal
- 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 Machine Learning to Machine Reasoning
- From Variational to Deterministic Autoencoders
- Functional regularisation for continual learning with gaussian processes
- Generating Image Descriptions
- Generating Random Numbers
- Generating text with recurrent neural networks
- Genetics
- GoingDeeperWithConvolutions
- Going Deeper with Convolutions
- GradientLess Descent
- Gradient Episodic Memory for Continual Learning
- Graph Laplacian Regularization for Larg-Scale Semidefinite Programming
- Graph Structure of Neural Networks
- 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
- Hash Embeddings for Efficient Word Representations
- Hierarchical Dirichlet Processes
- Hierarchical Question-Image Co-Attention for Visual Question Answering
- Hierarchical Representations for Efficient Architecture Search
- Human-level control through deep reinforcement learning
- IPBoost
- ImageNet Classification with Deep Convolutional Neural Networks
- Imagination-Augmented Agents for Deep Reinforcement Learning
- Imagination Augmented Agents for Deep Reinforcement Learning
- Importance Sampling June 2 2009
- Importance Sampling and Markov Chain Monte Carlo (MCMC)
- Importance Sampling and Monte Carlo Simulation
- 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
- 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
- Influenza Forecasting Framework based on Gaussian Processes
- Influenza Forecasting Framework based on Gaussian processes Summary
- 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
- Label-Free Supervision of Neural Networks with Physics and Domain Knowledge
- Large-Scale Supervised Sparse Principal Component Analysis
- Learning2reasoning
- Learning Combinatorial Optimzation
- Learning Convolutional Feature Hierarchies for Visual Recognition
- Learning Fast Approximations of Sparse Coding
- Learning Hierarchical Features for Scene Labeling
- Learning Long-Range Vision for Autonomous Off-Road Driving
- Learning Phrase Representations
- Learning Spectral Clustering, With Application To Speech Separation
- Learning The Difference That Makes A Difference With Counterfactually-Augmented Data
- Learning What and Where to Draw
- Learning a Nonlinear Embedding by Preserving Class Neighborhood Structure
- Learning the Number of Neurons in Deep Networks
- Learning to Navigate in Cities Without a Map
- Learning to Teach
- LightRNN: Memory and Computation-Efficient Recurrent Neural Networks
- Link to my paper
- Loss Function Search for Face Recognition
- MULTI-VIEW DATA GENERATION WITHOUT VIEW SUPERVISION
- MULTIPLE OBJECT RECOGNITION WITH VISUAL ATTENTION
- Main Page
- Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction
- Mark Your Contribution here
- Mark your contribution here
- Markov Chain Definitions
- Markov Random Fields for Super-Resolution
- MarrNet: 3D Shape Reconstruction via 2.5D Sketches
- Mask RCNN
- Matrix Completion with Noise
- Maximum-Margin Matrix Factorization
- Maximum Variance Unfolding (June 2 2009)
- Maximum likelihood estimation of intrinsic dimension
- Measuring Statistical Dependence with Hilbert-Schmidt Norm
- Measuring and testing dependence by correlation of distances
- Measuring statistical dependence with Hilbert-Schmidt norms
- Memory-Based Parameter Adaptation
- Memory Networks
- Meta-Learning-For-Domain Generalization
- Meta-Learning For Domain Generalization
- Metric and Kernel Learning Using a Linear Transformation
- Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
- ModelFramework.jpg
- Model Agnostic Learning of Semantic Features
- Modular Multitask Reinforcement Learning with Policy Sketches
- Monte Carlo Integration
- Monte Carlo methods
- Multi-Task Feature Learning
- Multi-scale Dense Networks for Resource Efficient Image Classification
- Music Recommender System Based using CRNN
- Natural language processing (almost) from scratch.
- Neighbourhood Components Analysis
- Neural Audio Synthesis of Musical Notes with WaveNet autoencoders
- Neural Machine Translation: Jointly Learning to Align and Translate
- Neural ODEs
- Neural Speed Reading
- Neural Speed Reading via Skim-RNN
- Neural Turing Machines
- Nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization
- Nonparametric Latent Feature Models for Link Prediction
- Obfuscated Gradients Give a False Sense of Security Circumventing Defenses to Adversarial Examples
- On The Convergence Of ADAM And Beyond
- On the Number of Linear Regions of Deep Neural Networks
- On the difficulty of training recurrent neural networks
- On using very large target vocabulary for neural machine translation
- One-Shot Imitation Learning
- One-Shot Object Detection with Co-Attention and Co-Excitation
- One pixel attack for fooling deep neural networks
- Optimal Solutions forSparse Principal Component Analysis
- Overfeat: integrated recognition, localization and detection using convolutional networks
- Paper 13
- Paper Summaries
- Parametric Local Metric Learning for Nearest Neighbor Classiﬁcation
- Parsing natural scenes and natural language with recursive neural networks
- 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
- Positive Semidefinite Metric Learning Using Boosting-like Algorithms
- 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
- Probabilistic Matrix Factorization
- Probabilistic PCA with GPLVM
- Proof
- Proof of Lemma 1
- Proof of Theorem 1
- Proposal Fall 2010
- Proposal for STAT946 (Deep Learning) final projects Fall 2015
- Proposal for STAT946 (Deep Learning) final projects Fall 2017
- Proposal for STAT946 projects
- Proposal for STAT946 projects Fall 2010
- Proposed Title
- Quantifying cancer progression with conjunctive Bayesian networks
- Quantifying cancer progression with conjunctive Bayesian networks.
- Question Answering with Subgraph Embeddings
- ROBPCA: A New Approach to Robust Principal Component Analysis
- Regression on Manifold using Kernel Dimension Reduction
- Regression on Manifolds Using Kernel Dimension Reduction
- Reinforcement Learning of Theorem Proving
- Relevant Component Analysis
- Representations of Words and Phrases and their Compositionality
- Research Papers Classification System
- Residual Component Analysis: Generalizing PCA for more flexible inference in linear-Gaussian models
- Roberta
- Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias
- Robust Imitation of Diverse Behaviors
- Robust Probabilistic Modeling with Bayesian Data Reweighting
- S13Stat946proposal
- STAT946F17/Cognitive Psychology For Deep Neural Networks: A Shape Bias Case Study
- STAT946F17/Conditional Image Generation with PixelCNN Decoders
- 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
- STAT946F17/cognitive psychology for deep neural networks a shape bias case study
- STAT946F20/BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
- Sandbox to test w2l
- Scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers Machines
- Schedule
- Schedule946
- Schedule of Project Presentations
- Searching For Efficient Multi Scale Architectures For Dense Image Prediction
- Self-Supervised Learning of Pretext-Invariant Representations
- Self-Taught Learning
- Semantic Relation Classification——via Convolution Neural Network
- Semi-supervised Learning with Deep Generative Models
- ShakeDrop Regularization
- Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
- Sign up for your presentation
- SignupformStat341F11
- Singular Value Decomposition(SVD)
- Sparse PCA
- Speech2Face: Learning the Face Behind a Voice
- Spherical CNNs
- Stat340s13
- Stat341
- Stat341 / CM 361
- Stat341f11
- Stat841
- Stat841f10
- Stat841f11
- Stat841f14
- Stat946
- Stat946-Fall 2010
- Stat946f10
- Stat946f11
- Stat946f11pool
- Stat946f15
- Stat946f15/Deep neural networks for acoustic modeling in speech recognition
- Stat946f15/Sequence to sequence learning with neural networks
- Stat946s13
- Statf09841Proposal
- Statf09841Scribe
- Statf10841Scribe
- Strategies for Training Large Scale Neural Network Language Models
- Streaming Bayesian Inference for Crowdsourced Classification
- Summary
- Summary - A Neural Representation of Sketch Drawings
- Summary for Saliency-based Sequential Image Attention with Multiset Prediction
- Summary for survey of neural networked-based cancer prediction models from microarray data
- SuperGLUE
- Superhuman AI for Multiplayer Poker
- Supervised Dictionary Learning
- Surround Vehicle Motion Prediction
- Synthesizing Programs for Images usingReinforced Adversarial Learning
- THE LOGICAL EXPRESSIVENESS OF GRAPH NEURAL NETWORKS
- TRIAL for that odd behaviour
- Task Understanding from Confushing Multitask Data
- Task Understanding from Confusing Multi-task Data
- Techniques for Normal and Gamma Sampling
- Test1
- Text Mining Classification Clustering Extraction Techniques
- The Curious Case of Degeneration
- The Indian Buffet Process: An Introduction and Review
- The Manifold Tangent Classifier
- The Wake-Sleep Algorithm for Unsupervised Neural Networks
- The loss surfaces of multilayer networks (Choromanska et al.)
- This Looks Like That: Deep Learning for Interpretable Image Recognition
- Time-series Generative Adversarial Networks
- Towards Deep Learning Models Resistant to Adversarial Attacks
- Training And Inference with Integers in Deep Neural Networks
- Uncovering Shared Structures in Multiclass Classification
- Understanding Image Motion with Group Representations