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Showing below up to 283 results in range #101 to #383.
- 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
- 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
- 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
- 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
- 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
- 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
- STAT946F20/BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
- 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 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
- 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
- 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
- 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 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 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
- adaptive dimension reduction for clustering high dimensional data
- again on Markov Chain
- 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
- 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
- f11Stat841EditorSignUp
- f11Stat841presentation
- f11Stat841proposal
- f11Stat946ass
- f11stat946EditorSignUp
- f14Stat842EditorSignUp
- from Machine Learning to Machine Reasoning
- generating text with recurrent neural networks
- genetics
- goingDeeperWithConvolutions
- graph Laplacian Regularization for Larg-Scale Semidefinite Programming
- 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
- incremental Learning, Clustering and Hierarchy Formation of Whole Body Motion Patterns using Adaptive Hidden Markov Chains(Summary)
- 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
- learn what not to learn
- learning2reasoning
- 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
- link to my paper
- mULTIPLE OBJECT RECOGNITION WITH VISUAL ATTENTION
- mark Your Contribution here
- mark your contribution here
- markov Random Fields for Super-Resolution
- matrix Completion with Noise
- maximum-Margin Matrix Factorization
- maximum Variance Unfolding (June 2 2009)
- maximum likelihood estimation of intrinsic dimension
- meProp: Sparsified Back Propagation for Accelerated Deep Learning with Reduced Overfitting
- measuring Statistical Dependence with Hilbert-Schmidt Norm
- measuring and testing dependence by correlation of distances
- measuring statistical dependence with Hilbert-Schmidt norms
- memory Networks
- metric and Kernel Learning Using a Linear Transformation
- monte Carlo methods
- multi-Task Feature Learning
- natural language processing (almost) from scratch.
- neighbourhood Components Analysis
- neural Machine Translation: Jointly Learning to Align and Translate
- neural Turing Machines
- nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization
- nonparametric Latent Feature Models for Link Prediction
- 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
- orthogonal gradient descent for continual learning
- overfeat: integrated recognition, localization and detection using convolutional networks
- paper 13
- parametric Local Metric Learning for Nearest Neighbor Classification
- parsing natural scenes and natural language with recursive neural networks
- policy optimization with demonstrations
- positive Semidefinite Metric Learning Using Boosting-like Algorithms
- 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 projects
- proposal for STAT946 projects Fall 2010
- 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
- relevant Component Analysis
- residual Component Analysis: Generalizing PCA for more flexible inference in linear-Gaussian models
- s13Stat946proposal
- sandbox to test w2l
- scene Parsing with Multiscale Feature Learning, Purity Trees, and Optimal Covers Machines
- schedule
- schedule946
- schedule of Project Presentations
- self-Taught Learning
- semi-supervised Learning with Deep Generative Models
- show, Attend and Tell: Neural Image Caption Generation with Visual Attention
- signupformStat341F11
- singular Value Decomposition(SVD)
- sparse PCA
- 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
- stat946f11pool
- stat946f15/Deep neural networks for acoustic modeling in speech recognition
- stat946f15/Sequence to sequence learning with neural networks
- stat946w18
- 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
- statf09841Proposal
- statf09841Scribe
- statf10841Scribe
- strategies for Training Large Scale Neural Network Language Models
- summary
- supervised Dictionary Learning
- tRIAL for that odd behaviour
- test
- 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.)
- time-series-using-GAN
- uncovering Shared Structures in Multiclass Classification
- very Deep Convoloutional Networks for Large-Scale Image Recognition
- video-Based Face Recognition Using Adaptive Hidden Markov Models
- visualizing Data using t-SNE
- visualizing Similarity Data with a Mixture of Maps
- what game are we playing
- wikicoursenote:Manual of Style
- wikicoursenote:cleanup
