Papers
11,015 papers found
Apprentice: Using Knowledge Distillation Techniques To Improve Low-Precision Network Accuracy
Asit Mishra, Debbie Marr
A Scalable Laplace Approximation for Neural Networks
Hippolyt Ritter, Aleksandar Botev, David Barber
A Simple Neural Attentive Meta-Learner
Nikhil Mishra, Mostafa Rohaninejad, Xi Chen et al.
Ask the Right Questions: Active Question Reformulation with Reinforcement Learning
Christian Buck, Jannis Bulian, Massimiliano Ciaramita et al.
Attacking Binarized Neural Networks
Angus Galloway, Graham W. Taylor, Medhat Moussa
Auto-Conditioned Recurrent Networks for Extended Complex Human Motion Synthesis
Yi Zhou, Zimo Li, Shuangjiu Xiao et al.
Auto-Encoding Sequential Monte Carlo
Tuan Anh Le, Maximilian Igl, Tom Rainforth et al.
Automatically Inferring Data Quality for Spatiotemporal Forecasting
Sungyong Seo, Arash Mohegh, George Ban-Weiss et al.
Backpropagation through the Void: Optimizing control variates for black-box gradient estimation
Will Grathwohl, Dami Choi, Yuhuai Wu et al.
Beyond Shared Hierarchies: Deep Multitask Learning through Soft Layer Ordering
Elliot Meyerson, Risto Miikkulainen
Beyond Word Importance: Contextual Decomposition to Extract Interactions from LSTMs
W. James Murdoch, Peter J. Liu, Bin Yu
Bi-Directional Block Self-Attention for Fast and Memory-Efficient Sequence Modeling
Tao Shen, Tianyi Zhou, Guodong Long et al.
Boosting Dilated Convolutional Networks with Mixed Tensor Decompositions
Nadav Cohen, Ronen Tamari, Amnon Shashua
Boosting the Actor with Dual Critic
Bo Dai, Albert Shaw, Niao He et al.
Boundary Seeking GANs
R Devon Hjelm, Athul Paul Jacob, Adam Trischler et al.
Breaking the Softmax Bottleneck: A High-Rank RNN Language Model
Zhilin Yang, Zihang Dai, Ruslan Salakhutdinov et al.
Can Neural Networks Understand Logical Entailment?
Richard Evans, David Saxton, David Amos et al.
Can recurrent neural networks warp time?
Corentin Tallec, Yann Ollivier
Cascade Adversarial Machine Learning Regularized with a Unified Embedding
Taesik Na, Jong Hwan Ko, Saibal Mukhopadhyay
CausalGAN: Learning Causal Implicit Generative Models with Adversarial Training
Murat Kocaoglu, Christopher Snyder, Alexandros G. Dimakis et al.
Certified Defenses against Adversarial Examples
Aditi Raghunathan, Jacob Steinhardt, Percy Liang
Certifying Some Distributional Robustness with Principled Adversarial Training
Aman Sinha, Hongseok Namkoong, John Duchi
cGANs with Projection Discriminator
Takeru Miyato, Masanori Koyama
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality
Xingjun Ma, Bo Li, Yisen Wang et al.
Combining Symbolic Expressions and Black-box Function Evaluations in Neural Programs
Forough Arabshahi, Sameer Singh, Animashree Anandkumar