oral:
149 Adversarial Feature Learning
147 Hierarchical Multiscale Recurrent Neural Networks
140 Recurrent Batch Normalization
80 HyperNetworks
79 FractalNet: Ultra-Deep Neural Networks without Residuals
73 Zoneout: Regularizing RNNs by Randomly Preserving Hidden Activations
64 Reinforcement Learning with Unsupervised Auxiliary Tasks
62 Unrolled Generative Adversarial Networks
60 Adversarial examples in the physical world
52 Adversarially Learned Inference
poster:
49 Quasi-Recurrent Neural Networks
48 Do Deep Convolutional Nets Really Need to be Deep and Convolutional?
46 The Predictron: End-To-End Learning and Planning
46 Neural Photo Editing with Introspective Adversarial Networks
44 Neural Architecture Search with Reinforcement Learning
43 An Actor-Critic Algorithm for Sequence Prediction
41 A Learned Representation For Artistic Style
39 RL^2: Fast Reinforcement Learning via Slow Reinforcement Learning
38 Understanding deep learning requires rethinking generalization
37 Structured Attention Networks
35 Understanding intermediate layers using linear classifier probes
33 Mollifying Networks
33 Hierarchical Memory Networks
31 Learning in Implicit Generative Models
31 An Analysis of Deep Neural Network Models for Practical Applications
30 DeepCoder: Learning to Write Programs
28 Towards Principled Methods for Training Generative Adversarial Networks
28 SGDR: Stochastic Gradient Descent with Warm Restarts
27 Learning to Navigate in Complex Environments
27 Generative Multi-Adversarial Networks
26 Soft Weight-Sharing for Neural Network Compression
25 Pruning Filters for Efficient ConvNets
24 Why Deep Neural Networks for Function Approximation?
24 Mode Regularized Generative Adversarial Networks
24 Dialogue Learning With Human-in-the-Loop
24 Designing Neural Network Architectures using Reinforcement Learning
23 PGQ: Combining policy gradient and Q-learning
22 Learning End-to-End Goal-Oriented Dialog
22 Frustratingly Short Attention Spans in Neural Language Modeling
21 Tracking the World State with Recurrent Entity Networks
21 Deep Probabilistic Programming
20 Low-rank passthrough neural networks
20 Density estimation using Real NVP
20 Adversarial Training Methods for Semi-Supervised Text Classification
19 Semi-Supervised Classification with Graph Convolutional Networks
19 Q-Prop: Sample-Efficient Policy Gradient with An Off-Policy Critic
19 PixelVAE: A Latent Variable Model for Natural Images
19 Learning to Optimize
19 Learning a Natural Language Interface with Neural Programmer
19 Higher Order Recurrent Neural Networks
19 Entropy-SGD: Biasing Gradient Descent Into Wide Valleys
19 Dynamic Coattention Networks For Question Answering
18 PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications
18 Generalizing Skills with Semi-Supervised Reinforcement Learning
18 Deep Learning with Dynamic Computation Graphs
18 Automatic Rule Extraction from Long Short Term Memory Networks
18 Adversarial Machine Learning at Scale
18 Adding Gradient Noise Improves Learning for Very Deep Networks
17 Learning through Dialogue Interactions by Asking Questions
16 Unsupervised Pretraining for Sequence to Sequence Learning
16 Surprise-Based Intrinsic Motivation for Deep Reinforcement Learning
16 Learning to Perform Physics Experiments via Deep Reinforcement Learning
16 Categorical Reparameterization with Gumbel-Softmax
16 A Joint Many-Task Model: Growing a Neural Network for Multiple NLP Tasks
15 Sample Efficient Actor-Critic with Experience Replay
15 Adversarial examples for generative models
14 Variational Lossy Autoencoder
14 Multiplicative LSTM for sequence modelling
14 Identity Matters in Deep Learning
14 Gated-Attention Readers for Text Comprehension
14 Bidirectional Attention Flow for Machine Comprehension
13 Towards a Neural Statistician
13 Recurrent Mixture Density Network for Spatiotemporal Visual Attention
13 On Detecting Adversarial Perturbations
13 Learning to Act by Predicting the Future
13 Extensions and Limitations of the Neural GPU
13 Efficient Softmax Approximation for GPUs
12 Warped Convolutions: Efficient Invariance to Spatial Transformations
12 Trained Ternary Quantization
12 RenderGAN: Generating Realistic Labeled Data
12 Improving Policy Gradient by Exploring Under-appreciated Rewards
12 Generalizable Features From Unsupervised Learning
12 Capacity and Trainability in Recurrent Neural Networks
12 Amortised MAP Inference for Image Super-resolution
11 SampleRNN: An Unconditional End-to-End Neural Audio Generation Model
11 Neural Combinatorial Optimization with Reinforcement Learning
11 Memory-augmented Attention Modelling for Videos
11 Machine Comprehension Using Match-LSTM and Answer Pointer
11 Latent Sequence Decompositions
11 Calibrating Energy-based Generative Adversarial Networks
10 Unsupervised Cross-Domain Image Generation
10 Programming With a Differentiable Forth Interpreter
10 Learning to Remember Rare Events
10 Highway and Residual Networks learn Unrolled Iterative Estimation
10 GRAM: Graph-based Attention Model for Healthcare Representation Learning
9 Wav2Letter: an End-to-End ConvNet-based Speech Recognition System
9 Understanding trained CNNs by indexing neuron selectivity
9 TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency
9 The Power of Sparsity in Convolutional Neural Networks
9 Steerable CNNs
9 Query-Reduction Networks for Question Answering
9 Lossy Image Compression with Compressive Autoencoders
9 Learning to Compose Words into Sentences with Reinforcement Learning
9 Improving Stochastic Gradient Descent with Feedback
8 Towards Information-Seeking Agents
8 Stick-Breaking Variational Autoencoders
8 NEWSQA: A MACHINE COMPREHENSION DATASET
8 Multi-Agent Cooperation and the Emergence of (Natural) Language
8 LipNet: End-to-End Sentence-level Lipreading
8 Gated Multimodal Units for Information Fusion
8 End-to-end Optimized Image Compression
8 Deep Variational Information Bottleneck
8 Deep Learning with Sets and Point Clouds
8 Batch Policy Gradient Methods for Improving Neural Conversation Models
7 Unsupervised Perceptual Rewards for Imitation Learning
7 Generative Adversarial Parallelization
7 Efficient Summarization with Read-Again and Copy Mechanism
7 Discrete Variational Autoencoders
7 Data Noising as Smoothing in Neural Network Language Models
6 Variable Computation in Recurrent Neural Networks
6 Sigma Delta Quantized Networks
6 Multi-task learning with deep model based reinforcement learning
6 Multi-modal Variational Encoder-Decoders
workshop:
6 End-to-End Answer Chunk Extraction and Ranking for Reading Comprehension
6 Dropout with Expectation-linear Regularization
6 Delving into Transferable Adversarial Examples and Black-box Attacks
6 Boosting Image Captioning with Attributes
6 Beyond Fine Tuning: A Modular Approach to Learning on Small Data
6 A Compositional Object-Based Approach to Learning Physical Dynamics
5 Towards the Limit of Network Quantization
5 Tighter bounds lead to improved classifiers
5 Structured Sequence Modeling with Graph Convolutional Recurrent Networks
5 Song From PI: A Musically Plausible Network for Pop Music Generation
5 Pointer Sentinel Mixture Models
5 On the Quantitative Analysis of Decoder-Based Generative Models
5 Neuro-Symbolic Program Synthesis
5 Modular Multitask Reinforcement Learning with Policy Sketches
5 Lie-Access Neural Turing Machines
5 Learning to superoptimize programs
5 Learning Features of Music From Scratch
5 Improving Neural Language Models with a Continuous Cache
5 Human perception in computer vision
5 Deep Biaffine Attention for Neural Dependency Parsing
5 Cooperative Training of Descriptor and Generator Networks
5 A Differentiable Physics Engine for Deep Learning in Robotics
4 Temporal Ensembling for Semi-Supervised Learning
reject:
4 Options Discovery with Budgeted Reinforcement Learning
4 Incremental Sequence Learning
4 FastText.zip: Compressing text classification models
4 Exponential Machines
4 Diet Networks: Thin Parameters for Fat Genomics
4 DeepDSL: A Compilation-based Domain-Specific Language for Deep Learning
4 Dataset Augmentation in Feature Space
4 DSD: Dense-Sparse-Dense Training for Deep Neural Networks
4 A recurrent neural network without chaos
3 Trusting SVM for Piecewise Linear CNNs
3 The Neural Noisy Channel
3 Simple Black-Box Adversarial Perturbations for Deep Networks
3 Sequence to Sequence Transduction with Hard Monotonic Attention
3 Semi-supervised deep learning by metric embedding
3 Revisiting Classifier Two-Sample Tests
3 Regularizing CNNs with Locally Constrained Decorrelations
3 Playing SNES in the Retro Learning Environment
3 Optimal Binary Autoencoding with Pairwise Correlations
3 Multi-view Generative Adversarial Networks
3 Loss-aware Binarization of Deep Networks
3 Learning Recurrent Representations for Hierarchical Behavior Modeling
3 Joint Multimodal Learning with Deep Generative Models
3 Here's My Point: Argumentation Mining with Pointer Networks
3 EPOpt: Learning Robust Neural Network Policies Using Model Ensembles
3 Deep Information Propagation
3 Boosted Generative Models
3 Attentive Recurrent Comparators
2 Words or Characters? Fine-grained Gating for Reading Comprehension
2 Two Methods for Wild Variational Inference
2 Topology and Geometry of Half-Rectified Network Optimization
2 Maximum Entropy Flow Networks
2 Incorporating long-range consistency in CNN-based texture generation
2 Hadamard Product for Low-rank Bilinear Pooling
2 Fast Adaptation in Generative Models with Generative Matching Networks
2 Efficient iterative policy optimization
2 Adaptive Feature Abstraction for Translating Video to Language
1 Reference-Aware Language Models
1 Neural Machine Translation with Latent Semantic of Image and Text
1 Near-Data Processing for Machine Learning
1 Multi-view Recurrent Neural Acoustic Word Embeddings
1 Modularized Morphing of Neural Networks
1 Learning Continuous Semantic Representations of Symbolic Expressions
1 Intelligible Language Modeling with Input Switched Affine Networks
1 Inductive Bias of Deep Convolutional Networks through Pooling Geometry
1 Geometry of Polysemy
1 Generating Long and Diverse Responses with Neural Conversation Models
1 Extrapolation and learning equations
1 Deep Generalized Canonical Correlation Analysis
1 Autoencoding Variational Inference For Topic Models
1 A STRUCTURED SELF-ATTENTIVE SENTENCE EMBEDDING
1 A Context-aware Attention Network for Interactive Question Answering
0 Transformation-based Models of Video Sequences
0 Online Structure Learning for Sum-Product Networks with Gaussian Leaves
0 Exploring LOTS in Deep Neural Networks
0 Deep Multi-task Representation Learning: A Tensor Factorisation Approach
0 Bit-Pragmatic Deep Neural Network Computing
0 Annealing Gaussian into ReLU: a New Sampling Strategy for Leaky-ReLU RBM
0 A Compare-Aggregate Model for Matching Text Sequences