Papers
LoopReg: Self-supervised Learning of Implicit Surface Correspondences, Pose and Shape for 3D Human Mesh Registration
Bharat Lal Bhatnagar, Cristian Sminchisescu, Christian Theobalt et al.
Reward Propagation Using Graph Convolutional Networks
Martin Klissarov, Doina Precup
Path Sample-Analytic Gradient Estimators for Stochastic Binary Networks
Alexander Shekhovtsov, Viktor Yanush, Boris Flach
Walking in the Shadow: A New Perspective on Descent Directions for Constrained Minimization
Hassan Mortagy, Swati Gupta, Sebastian Pokutta
Breaking the Sample Size Barrier in Model-Based Reinforcement Learning with a Generative Model
Gen Li, Yuting Wei, Yuejie Chi et al.
Practical No-box Adversarial Attacks against DNNs
Qizhang Li, Yiwen Guo, Hao Chen
ConvBERT: Improving BERT with Span-based Dynamic Convolution
Zi-Hang Jiang, Weihao Yu, Daquan Zhou et al.
Uncertainty Aware Semi-Supervised Learning on Graph Data
Xujiang Zhao, Feng Chen, Shu Hu et al.
Non-parametric Models for Non-negative Functions
Ulysse Marteau-Ferey, Francis R. Bach, Alessandro Rudi
f-GAIL: Learning f-Divergence for Generative Adversarial Imitation Learning
Xin Zhang, Yanhua Li, Ziming Zhang et al.
CogLTX: Applying BERT to Long Texts
Ming Ding, Chang Zhou, Hongxia Yang et al.
Testing Determinantal Point Processes
Khashayar Gatmiry, Maryam Aliakbarpour, Stefanie Jegelka
ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA
Ilyes Khemakhem, Ricardo Monti, Diederik Kingma et al.
Stochastic Segmentation Networks: Modelling Spatially Correlated Aleatoric Uncertainty
Miguel Monteiro, Loic Le Folgoc, Daniel Coelho de Castro et al.
Probabilistic Fair Clustering
Seyed Esmaeili, Brian Brubach, Leonidas Tsepenekas et al.
Multi-Stage Influence Function
Hongge Chen, Si Si, Yang Li et al.
Incorporating Interpretable Output Constraints in Bayesian Neural Networks
Wanqian Yang, Lars Lorch, Moritz Graule et al.
Revisiting the Sample Complexity of Sparse Spectrum Approximation of Gaussian Processes
Minh Hoang, Nghia Hoang, Hai Pham et al.
Learning Causal Effects via Weighted Empirical Risk Minimization
Yonghan Jung, Jin Tian, Elias Bareinboim
SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows
Didrik Nielsen, Priyank Jaini, Emiel Hoogeboom et al.
GS-WGAN: A Gradient-Sanitized Approach for Learning Differentially Private Generators
Dingfan Chen, Tribhuvanesh Orekondy, Mario Fritz
Adversarially-learned Inference via an Ensemble of Discrete Undirected Graphical Models
Adarsh Keshav Jeewajee, Leslie P. Kaelbling
Robust Gaussian Covariance Estimation in Nearly-Matrix Multiplication Time
Jerry Li, Guanghao Ye
Joint Contrastive Learning with Infinite Possibilities
Qi Cai, Yu Wang, Yingwei Pan et al.
Forget About the LiDAR: Self-Supervised Depth Estimators with MED Probability Volumes
Juan Luis GonzalezBello, Munchurl Kim