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Showing below up to 50 results in range #41 to #90.
- (hist) learn what not to learn [29,756 bytes]
- (hist) Being Bayesian about Categorical Probability [29,729 bytes]
- (hist) STAT946F17/ Improved Variational Inference with Inverse Autoregressive Flow [29,726 bytes]
- (hist) stat946w18/Towards Image Understanding From Deep Compression Without Decoding [29,622 bytes]
- (hist) Mapping Images to Scene Graphs with Permutation-Invariant Structured Prediction [29,570 bytes]
- (hist) Surround Vehicle Motion Prediction [29,510 bytes]
- (hist) Evaluating Machine Accuracy on ImageNet [29,340 bytes]
- (hist) End to end Active Object Tracking via Reinforcement Learning [29,206 bytes]
- (hist) Imagination-Augmented Agents for Deep Reinforcement Learning [29,197 bytes]
- (hist) stat946w18/Unsupervised Machine Translation Using Monolingual Corpora Only [29,141 bytes]
- (hist) Unsupervised Neural Machine Translation [28,860 bytes]
- (hist) Learning to Navigate in Cities Without a Map [28,789 bytes]
- (hist) LightRNN: Memory and Computation-Efficient Recurrent Neural Networks [28,750 bytes]
- (hist) Summary of A Probabilistic Approach to Neural Network Pruning [28,196 bytes]
- (hist) proposal Fall 2010 [28,170 bytes]
- (hist) Hierarchical Question-Image Co-Attention for Visual Question Answering [28,143 bytes]
- (hist) Task Understanding from Confusing Multi-task Data [27,980 bytes]
- (hist) Research Papers Classification System [27,978 bytes]
- (hist) stat946F18/differentiableplasticity [27,749 bytes]
- (hist) DON'T DECAY THE LEARNING RATE , INCREASE THE BATCH SIZE [27,357 bytes]
- (hist) Neural Speed Reading via Skim-RNN [27,299 bytes]
- (hist) measuring Statistical Dependence with Hilbert-Schmidt Norm [27,247 bytes]
- (hist) Obfuscated Gradients Give a False Sense of Security Circumventing Defenses to Adversarial Examples [27,233 bytes]
- (hist) Adacompress: Adaptive compression for online computer vision services [27,197 bytes]
- (hist) Convolutional Sequence to Sequence Learning [27,188 bytes]
- (hist) Understanding the Effective Receptive Field in Deep Convolutional Neural Networks [27,163 bytes]
- (hist) STAT946F17/ Learning a Probabilistic Latent Space of Object Shapes via 3D GAN [27,054 bytes]
- (hist) Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks [26,931 bytes]
- (hist) f11Stat841proposal [26,834 bytes]
- (hist) Robot Learning in Homes: Improving Generalization and Reducing Dataset Bias [26,820 bytes]
- (hist) Functional regularisation for continual learning with gaussian processes [26,792 bytes]
- (hist) Loss Function Search for Face Recognition [26,747 bytes]
- (hist) regression on Manifold using Kernel Dimension Reduction [26,560 bytes]
- (hist) f10 Stat841 digest [26,540 bytes]
- (hist) Superhuman AI for Multiplayer Poker [26,382 bytes]
- (hist) Music Recommender System Based using CRNN [26,359 bytes]
- (hist) Visual Reinforcement Learning with Imagined Goals [26,330 bytes]
- (hist) stat946w18/Wavelet Pooling For Convolutional Neural Networks [26,185 bytes]
- (hist) Dialog-based Language Learning [26,148 bytes]
- (hist) what game are we playing [25,901 bytes]
- (hist) Summary for survey of neural networked-based cancer prediction models from microarray data [25,813 bytes]
- (hist) human-level control through deep reinforcement learning [25,775 bytes]
- (hist) Summary - A Neural Representation of Sketch Drawings [25,539 bytes]
- (hist) Universal Style Transfer via Feature Transforms [25,427 bytes]
- (hist) graves et al., Speech recognition with deep recurrent neural networks [25,222 bytes]
- (hist) stat946w18/Tensorized LSTMs [25,187 bytes]
- (hist) Learning the Number of Neurons in Deep Networks [25,059 bytes]
- (hist) consistency of Trace Norm Minimization [24,984 bytes]
- (hist) MULTI-VIEW DATA GENERATION WITHOUT VIEW SUPERVISION [24,968 bytes]
- (hist) Neural ODEs [24,911 bytes]