Papers
11,015 papers found
GENERATING HIGH FIDELITY IMAGES WITH SUBSCALE PIXEL NETWORKS AND MULTIDIMENSIONAL UPSCALING
Jacob Menick, Nal Kalchbrenner
Generating Liquid Simulations with Deformation-aware Neural Networks
Lukas Prantl, Boris Bonev, Nils Thuerey
Generating Multi-Agent Trajectories using Programmatic Weak Supervision
Eric Zhan, Stephan Zheng, Yisong Yue et al.
Generating Multiple Objects at Spatially Distinct Locations
Tobias Hinz, Stefan Heinrich, Stefan Wermter
Generative Code Modeling with Graphs
Marc Brockschmidt, Miltiadis Allamanis, Alexander L. Gaunt et al.
Generative predecessor models for sample-efficient imitation learning
Yannick Schroecker, Mel Vecerik, Jon Scholz
Generative Question Answering: Learning to Answer the Whole Question
Mike Lewis, Angela Fan
Global-to-local Memory Pointer Networks for Task-Oriented Dialogue
Chien-Sheng Wu, Richard Socher, Caiming Xiong
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding
Alex Wang, Amanpreet Singh, Julian Michael et al.
GO Gradient for Expectation-Based Objectives
Yulai Cong, Miaoyun Zhao, Ke Bai et al.
Gradient descent aligns the layers of deep linear networks
Ziwei Ji, Matus Telgarsky
Gradient Descent Provably Optimizes Over-parameterized Neural Networks
Simon S. Du, Xiyu Zhai, Barnabas Poczos et al.
Graph HyperNetworks for Neural Architecture Search
Chris Zhang, Mengye Ren, Raquel Urtasun
Graph Wavelet Neural Network
Bingbing Xu, Huawei Shen, Qi Cao et al.
G-SGD: Optimizing ReLU Neural Networks in its Positively Scale-Invariant Space
Qi Meng, Shuxin Zheng, Huishuai Zhang et al.
Guiding Policies with Language via Meta-Learning
John D. Co-Reyes, Abhishek Gupta, Suvansh Sanjeev et al.
Harmonic Unpaired Image-to-image Translation
Rui Zhang, Tomas Pfister, Jia Li
Harmonizing Maximum Likelihood with GANs for Multimodal Conditional Generation
Soochan Lee, Junsoo Ha, Gunhee Kim
h-detach: Modifying the LSTM Gradient Towards Better Optimization
Bhargav Kanuparthi, Devansh Arpit, Giancarlo Kerg et al.
Hierarchical Generative Modeling for Controllable Speech Synthesis
Wei-Ning Hsu, Yu Zhang, Ron J. Weiss et al.
Hierarchical interpretations for neural network predictions
Chandan Singh, W. James Murdoch, Bin Yu
Hierarchical Reinforcement Learning via Advantage-Weighted Information Maximization
Takayuki Osa, Voot Tangkaratt, Masashi Sugiyama
Hierarchical RL Using an Ensemble of Proprioceptive Periodic Policies
Kenneth Marino, Abhinav Gupta, Rob Fergus et al.
Hierarchical Visuomotor Control of Humanoids
Josh Merel, Arun Ahuja, Vu Pham et al.
Hindsight policy gradients
Paulo Rauber, Avinash Ummadisingu, Filipe Mutz et al.