Papers
Deep Network for the Integrated 3D Sensing of Multiple People in Natural Images
Andrei Zanfir, Elisabeta Marinoiu, Mihai Zanfir et al.
Deep Neural Nets with Interpolating Function as Output Activation
Bao Wang, Xiyang Luo, Zhen Li et al.
Deep Neural Networks with Box Convolutions
Egor Burkov, Victor Lempitsky
Deep Non-Blind Deconvolution via Generalized Low-Rank Approximation
Wenqi Ren, Jiawei Zhang, Lin Ma et al.
DeepPINK: reproducible feature selection in deep neural networks
Yang Lu, Yingying Fan, Jinchi Lv et al.
Deep Poisson gamma dynamical systems
Dandan Guo, Bo Chen, Hao Zhang et al.
Deep Predictive Coding Network with Local Recurrent Processing for Object Recognition
Kuan Han, Haiguang Wen, Yizhen Zhang et al.
DeepProbLog: Neural Probabilistic Logic Programming
Robin Manhaeve, Sebastijan Dumancic, Angelika Kimmig et al.
Deep Reinforcement Learning in a Handful of Trials using Probabilistic Dynamics Models
Kurtland Chua, Roberto Calandra, Rowan McAllister et al.
Deep Reinforcement Learning of Marked Temporal Point Processes
Utkarsh Upadhyay, Abir De, Manuel Gomez Rodriguez
Deep State Space Models for Time Series Forecasting
Syama Sundar Rangapuram, Matthias W Seeger, Jan Gasthaus et al.
Deep State Space Models for Unconditional Word Generation
Florian Schmidt, Thomas Hofmann
Deep Structured Prediction with Nonlinear Output Transformations
Colin Graber, Ofer Meshi, Alexander Schwing
Delta-encoder: an effective sample synthesis method for few-shot object recognition
Eli Schwartz, Leonid Karlinsky, Joseph Shtok et al.
Demystifying excessively volatile human learning: A Bayesian persistent prior and a neural approximation
Chaitanya Ryali, Gautam Reddy, Angela J. Yu
Dendritic cortical microcircuits approximate the backpropagation algorithm
João Sacramento, Rui Ponte Costa, Yoshua Bengio et al.
Densely Connected Attention Propagation for Reading Comprehension
Yi Tay, Anh Tuan Luu, Siu Cheung Hui et al.
Depth-Limited Solving for Imperfect-Information Games
Noam Brown, Tuomas Sandholm, Brandon Amos
Derivative Estimation in Random Design
Yu Liu, Kris De Brabanter
Designing by Training: Acceleration Neural Network for Fast High-Dimensional Convolution
Longquan Dai, Liang Tang, Yuan Xie et al.
Dialog-based Interactive Image Retrieval
Xiaoxiao Guo, Hui Wu, Yu Cheng et al.
Dialog-to-Action: Conversational Question Answering Over a Large-Scale Knowledge Base
Daya Guo, Duyu Tang, Nan Duan et al.
Differentiable MPC for End-to-end Planning and Control
Brandon Amos, Ivan Jimenez, Jacob Sacks et al.
Differentially Private Bayesian Inference for Exponential Families
Garrett Bernstein, Daniel R. Sheldon
Differentially Private Change-Point Detection
Rachel Cummings, Sara Krehbiel, Yajun Mei et al.