Papers
Efficient Amortised Bayesian Inference for Hierarchical and Nonlinear Dynamical Systems
Geoffrey Roeder, Paul Grant, Andrew Phillips et al.
Graphical-model based estimation and inference for differential privacy
Ryan Mckenna, Daniel Sheldon, Gerome Miklau
Distributional Reinforcement Learning for Efficient Exploration
Borislav Mavrin, Hengshuai Yao, Linglong Kong et al.
MIWAE: Deep Generative Modelling and Imputation of Incomplete Data Sets
Pierre-Alexandre Mattei, Jes Frellsen
Disentangling Disentanglement in Variational Autoencoders
Emile Mathieu, Tom Rainforth, N Siddharth et al.
Optimal Minimal Margin Maximization with Boosting
Alexander Mathiasen, Kasper Green Larsen, Allan Grønlund
Fairness-Aware Learning for Continuous Attributes and Treatments
Jeremie Mary, Clément Calauzènes, Noureddine El Karoui
Decomposing feature-level variation with Covariate Gaussian Process Latent Variable Models
Kaspar Märtens, Kieran Campbell, Christopher Yau
On the Universality of Invariant Networks
Haggai Maron, Ethan Fetaya, Nimrod Segol et al.
Adversarial Generation of Time-Frequency Features with application in audio synthesis
Andrés Marafioti, Nathanaël Perraudin, Nicki Holighaus et al.
A Baseline for Any Order Gradient Estimation in Stochastic Computation Graphs
Jingkai Mao, Jakob Foerster, Tim Rocktäschel et al.
Passed & Spurious: Descent Algorithms and Local Minima in Spiked Matrix-Tensor Models
Stefano Sarao Mannelli, Florent Krzakala, Pierfrancesco Urbani et al.
Learning from Delayed Outcomes via Proxies with Applications to Recommender Systems
Timothy Arthur Mann, Sven Gowal, Andras Gyorgy et al.
Calibrated Model-Based Deep Reinforcement Learning
Ali Malik, Volodymyr Kuleshov, Jiaming Song et al.
Breaking the gridlock in Mixture-of-Experts: Consistent and Efficient Algorithms
Ashok Makkuva, Pramod Viswanath, Sreeram Kannan et al.
Curvature-Exploiting Acceleration of Elastic Net Computations
Vien Mai, Mikael Johansson
Traditional and Heavy Tailed Self Regularization in Neural Network Models
Michael Mahoney, Charles Martin
Universal Multi-Party Poisoning Attacks
Saeed Mahloujifar, Mohammad Mahmoody, Ameer Mohammed
Guided evolutionary strategies: augmenting random search with surrogate gradients
Niru Maheswaranathan, Luke Metz, George Tucker et al.
Composable Core-sets for Determinant Maximization: A Simple Near-Optimal Algorithm
Sepideh Mahabadi, Piotr Indyk, Shayan Oveis Gharan et al.
Bayesian leave-one-out cross-validation for large data
Måns Magnusson, Michael Andersen, Johan Jonasson et al.
EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE
Chao Ma, Sebastian Tschiatschek, Konstantina Palla et al.
Variational Implicit Processes
Chao Ma, Yingzhen Li, Jose Miguel Hernandez-Lobato
Disentangled Graph Convolutional Networks
Jianxin Ma, Peng Cui, Kun Kuang et al.
Differentiable Dynamic Normalization for Learning Deep Representation
Ping Luo, Peng Zhanglin, Shao Wenqi et al.