Papers
Deep Automodulators
Ari Heljakka, Yuxin Hou, Juho Kannala et al.
Deep Diffusion-Invariant Wasserstein Distributional Classification
Sung Woo Park, Dong Wook Shu, Junseok Kwon
Deep Direct Likelihood Knockoffs
Mukund Sudarshan, Wesley Tansey, Rajesh Ranganath
Deep Energy-based Modeling of Discrete-Time Physics
Takashi Matsubara, Ai Ishikawa, Takaharu Yaguchi
Deep Evidential Regression
Alexander Amini, Wilko Schwarting, Ava Soleimany et al.
Deep Graph Pose: a semi-supervised deep graphical model for improved animal pose tracking
Anqi Wu, Estefany Kelly Buchanan, Matthew Whiteway et al.
DeepI2I: Enabling Deep Hierarchical Image-to-Image Translation by Transferring from GANs
yaxing wang, Lu Yu, Joost van de Weijer
Deep Imitation Learning for Bimanual Robotic Manipulation
Fan Xie, Alexander Chowdhury, M. Clara De Paolis Kaluza et al.
Deep Inverse Q-learning with Constraints
Gabriel Kalweit, Maria Huegle, Moritz Werling et al.
Deep learning versus kernel learning: an empirical study of loss landscape geometry and the time evolution of the Neural Tangent Kernel
Stanislav Fort, Gintare Karolina Dziugaite, Mansheej Paul et al.
Deeply Learned Spectral Total Variation Decomposition
Tamara G. Grossmann, Yury Korolev, Guy Gilboa et al.
Deep Metric Learning with Spherical Embedding
Dingyi Zhang, Yingming Li, Zhongfei Zhang
Deep Multimodal Fusion by Channel Exchanging
Yikai Wang, Wenbing Huang, Fuchun Sun et al.
Deep Rao-Blackwellised Particle Filters for Time Series Forecasting
Richard Kurle, Syama Sundar Rangapuram, Emmanuel de Bézenac et al.
Deep reconstruction of strange attractors from time series
William Gilpin
Deep Reinforcement and InfoMax Learning
Bogdan Mazoure, Remi Tachet des Combes, Thang Long Doan et al.
Deep Reinforcement Learning with Stacked Hierarchical Attention for Text-based Games
Yunqiu Xu, Meng Fang, Ling Chen et al.
Deep Relational Topic Modeling via Graph Poisson Gamma Belief Network
Chaojie Wang, Hao Zhang, Bo Chen et al.
Deep Shells: Unsupervised Shape Correspondence with Optimal Transport
Marvin Eisenberger, Aysim Toker, Laura Leal-Taixé et al.
Deep Smoothing of the Implied Volatility Surface
Damien Ackerer, Natasa Tagasovska, Thibault Vatter
Deep Statistical Solvers
Balthazar Donon, Zhengying Liu, Wenzhuo LIU et al.
Deep Structural Causal Models for Tractable Counterfactual Inference
Nick Pawlowski, Daniel Coelho de Castro, Ben Glocker
Deep Subspace Clustering with Data Augmentation
Mahdi Abavisani, Alireza Naghizadeh, Dimitris Metaxas et al.
DeepSVG: A Hierarchical Generative Network for Vector Graphics Animation
Alexandre Carlier, Martin Danelljan, Alexandre Alahi et al.
Deep Transformation-Invariant Clustering
Tom Monnier, Thibault Groueix, Mathieu Aubry