| 2018 | Variational Inference for Gaussian Process Models for Survival Analysis. | Minyoung Kim, Vladimir Pavlovic |
| 2018 | Fast Counting in Machine Learning Applications. | Subhadeep Karan, Matthew Eichhorn, Blake Hurlburt, Grant Iraci, Jaroslaw Zola |
| 2018 | Transferable Meta Learning Across Domains. | Bingyi Kang, Jiashi Feng |
| 2018 | Finite-State Controllers of POMDPs using Parameter Synthesis. | Sebastian Junges, Nils Jansen, Ralf Wimmer, Tim Quatmann, Leonore Winterer, Joost-Pieter Katoen, Bernd Becker |
| 2018 | Testing for Conditional Mean Independence with Covariates through Martingale Difference Divergence. | Ze Jin, Xiaohan Yan, David S. Matteson |
| 2018 | Causal Identification under Markov Equivalence. | Amin Jaber, Jiji Zhang, Elias Bareinboim |
| 2018 | Averaging Weights Leads to Wider Optima and Better Generalization. | Pavel Izmailov, Dmitrii Podoprikhin, Timur Garipov, Dmitry P. Vetrov, Andrew Gordon Wilson |
| 2018 | Unsupervised Multi-view Nonlinear Graph Embedding. | Jiaming Huang, Zhao Li, Vincent W. Zheng, Wen Wen, Yifan Yang, Yuanmi Chen |
| 2018 | The Variational Homoencoder: Learning to learn high capacity generative models from few examples. | Luke B. Hewitt, Maxwell I. Nye, Andreea Gane, Tommi S. Jaakkola, Joshua B. Tenenbaum |
| 2018 | Variational zero-inflated Gaussian processes with sparse kernels. | Pashupati Hegde, Markus Heinonen, Samuel Kaski |
| 2018 | Fast Kernel Approximations for Latent Force Models and Convolved Multiple-Output Gaussian processes. | Cristian Guarnizo, Mauricio A. lvarez |
| 2018 | Structured nonlinear variable selection. | Magda Gregorova, Alexandros Kalousis, Stphane Marchand-Maillet |
| 2018 | Discrete Sampling using Semigradient-based Product Mixtures. | Alkis Gotovos, S. Hamed Hassani, Andreas Krause, Stefanie Jegelka |
| 2018 | Stochastic Learning for Sparse Discrete Markov Random Fields with Controlled Gradient Approximation Error. | Sinong Geng, Zhaobin Kuang, Jie Liu, Stephen J. Wright, David Page |
| 2018 | Sparse Multi-Prototype Classification. | Vikas K. Garg, Lin Xiao, Ofer Dekel |
| 2018 | KBlrn: End-to-End Learning of Knowledge Base Representations with Latent, Relational, and Numerical Features. | Alberto Garca-Durn, Mathias Niepert |
| 2018 | Constraint-based Causal Discovery for Non-Linear Structural Causal Models with Cycles and Latent Confounders. | Patrick Forr, Joris M. Mooij |
| 2018 | Improved Stochastic Trace Estimation using Mutually Unbiased Bases. | Jack K. Fitzsimons, Michael A. Osborne, Stephen J. Roberts, Joseph Francis Fitzsimons |
| 2018 | Combinatorial Bandits for Incentivizing Agents with Dynamic Preferences. | Tanner Fiez, Shreyas Sekar, Liyuan Zheng, Lillian J. Ratliff |
| 2018 | Bayesian optimization and attribute adjustment. | Stephan Eismann, Daniel Levy, Rui Shu, Stefan Bartzsch, Stefano Ermon |
| 2018 | A Dual Approach to Scalable Verification of Deep Networks. | Krishnamurthy Dvijotham, Robert Stanforth, Sven Gowal, Timothy A. Mann, Pushmeet Kohli |
| 2018 | Efficient Bayesian Inference for a Gaussian Process Density Model. | Christian Donner, Manfred Opper |
| 2018 | Variational Inference for Gaussian Processes with Panel Count Data. | Hongyi Ding, Young Lee, Issei Sato, Masashi Sugiyama |
| 2018 | Soft-Robust Actor-Critic Policy-Gradient. | Esther Derman, Daniel J. Mankowitz, Timothy A. Mann, Shie Mannor |
| 2018 | Incremental Learning-to-Learn with Statistical Guarantees. | Giulia Denevi, Carlo Ciliberto, Dimitris Stamos, Massimiliano Pontil |