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Showing below up to 250 results in range #61 to #310.
- 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
- Extreme Multi-label Text Classification
- F18-STAT841-Proposal
- F18-STAT946-Proposal
- F21-STAT 441/841 CM 763-Proposal
- F21-STAT 940-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 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
- Hierarchical Representations for Efficient Architecture Search
- 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 What and Where to Draw
- 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
- 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
- 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 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 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
- adaptive dimension reduction for clustering high dimensional data
- again on Markov Chain
- bayesian and Frequentist Schools of Thought
- binomial Probability Monte Carlo Sampling June 2 2009
- compressive Sensing
- conditional neural process
- consistency of Trace Norm Minimization
- context Adaptive Training with Factorized Decision Trees for HMM-Based Speech Synthesis
- 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
- copyofstat341
- decentralised Data Fusion: A Graphical Model Approach (Summary)
- deepGenerativeModels
- deep Convolutional Neural Networks For LVCSR
- deep Learning of the tissue-regulated splicing code
- 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
- f11Stat841EditorSignUp
- f11Stat841presentation
- f11Stat841proposal
- f11Stat946papers
- f11Stat946presentation
- f11stat946EditorSignUp
- f14Stat842EditorSignUp
- f15Stat946PaperSignUp
- f17Stat946PaperSignUp
- generating Random Numbers
- genetics
- hamming Distance Metric Learning
- hierarchical Dirichlet Processes
- 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
- is Multinomial PCA Multi-faceted Clustering or Dimensionality Reduction
- kernel Dimension Reduction in Regression
- kernel Spectral Clustering for Community Detection in Complex Networks
- kernelized Locality-Sensitive Hashing
- kernelized Sorting
- learn what not to learn
- learning2reasoning
- learning Convolutional Feature Hierarchies for Visual Recognition
- learning Fast Approximations of Sparse Coding
- learning Spectral Clustering, With Application To Speech Separation
- learning a Nonlinear Embedding by Preserving Class Neighborhood Structure
- link to my paper
- mULTIPLE OBJECT RECOGNITION WITH VISUAL ATTENTION
- main Page
- mark Your Contribution here
- mark your contribution here
- markov Chain Definitions
- 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
- monte Carlo Integration
- monte Carlo methods
- neighbourhood Components Analysis
- neural Machine Translation: Jointly Learning to Align and Translate
- nonlinear Dimensionality Reduction by Semidefinite Programming and Kernel Matrix Factorization
- nonparametric Latent Feature Models for Link Prediction
- 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
- paper Summaries
- policy optimization with demonstrations
- 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.
- 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
- show, Attend and Tell: Neural Image Caption Generation with Visual Attention
- sign up for your presentation
- signupformStat341F11
- singular Value Decomposition(SVD)
- sparse PCA
- stat441F18
- stat441F18/TCNLM
- stat441F18/YOLO
- stat441F21
- stat441w18
- stat441w18/A New Method of Region Embedding for Text Classification
