Papers
Learning to Infer Fast by Attending to Sparse Temporal Observations
Mehrnaz Motamed, Harry Bendekgey, Debora Sujono et al.
Causal Reasoning with Bipartite Graphical Causal Models
Joris M. Mooij
Wasserstein Gradient Flows for Scalable and Regularized Barycenter Computation
Eduardo Fernandes Montesuma, Yassir Bendou, Mike Gartrell
Learning Stable Digraphs from Sparse-Input Linear Structural Causal Models
Panagiotis Misiakos, Markus Püschel
Long term sequential decision making under risk
Mohammad Mirzanejad, Nadjet Bourdache, Abdel-illah Mouaddib
Robust estimation of graphical models with measurement error: False discovery control and sensitivity analysis
Shira Mingelgrin, Y. Samuel Wang
Globally Optimal Multi-Object Tracking with Splitting and Merging
Mihaela Mihaylova, Jelle Piepenbrock, Johannes Textor
Exact Uncertainty Propagation via Gaussian Process Neurons
Qiuxian Meng, Yongyou Zhang
Conformal Graph Prediction with Z-Gromov Wasserstein Distances
Gabriel Melo, Thibaut de Saivre, Anna Calissano et al.
Causal Discovery in Mixtures of Populations
Bijan Mazaheri, Spencer L. Gordon, Yuval Rabani et al.
Relaxing Faithfulness with Intervention-Only Causal Discovery
Bijan Mazaheri, Jiaqi Zhang, Caroline Uhler
Meta-Dependence in Conditional Independence Testing
Bijan Mazaheri, Jiaqi Zhang, Caroline Uhler
Provable Guarantees For Robust Feature Selection in Sparse Linear Models in High-Dimensions
Deepak Maurya, Adarsh Barik, Jean Honorio
AudiFair: Privacy-Preserving Framework for Auditing Fairness
Elisaweta Masserova, Kshitij Kulkarni, Antigoni Polychroniadou et al.
cc-Shapley: Measuring Multivariate Feature Importance Needs Causal Context
Jörg Martin, Stefan Haufe
Learning Latent Energy-Based Models via Interacting Particle Langevin Dynamics
Joanna Marks, Tim Y. J. Wang, Omer Deniz Akyildiz
Learning plug-in surrogate endpoints for randomized experiments
Alessandro-Umberto Margueritte, Ahmet Zahid Balcıoğlu, Jesse H. Krijthe et al.
Information-Theoretic Lower Bounds for Causal Inference under Credal Uncertainty
Hung Mai, Hai Nguyen, Khanh Nguyen et al.
Approximating Nash Equilibria in Finite-Horizon Multi-Adversarial Team Markov Games
Prasanna Maddila, Régis Sabbadin, Meritxell Vinyals
Bayesian Causal Discovery in Directed Cyclic Graphs with Closed-Form Lag Bayes Factors
Seyed Reza Maadi, Sally Cripps
Learning Expressive Random Feature Models via Parametrized Activations
Zailin Ma, Jiansheng Yang, Yaodong Yang
First-Order Softmax Weighted Switching Gradient Method for Distributed Stochastic Minimax Optimization with Stochastic Constraints
Zhankun Luo, Antesh Upadhyay, Sang Bin Moon et al.
The relative value of interventional and observational samples in Bayesian Causal Linear Gaussian Models
Valentinian Mihai Lungu, Anish Dhir, Mark van der Wilk et al.
Computing Exact Nash Equilibria in Graphical Games: A Geometric Approach to Paths, Stars, and Caterpillars
Evan Lucca, Mohammad T. Irfan, Luis E. Ortiz
Conformal Prediction Sets for Instance Segmentation
Kerri Lu, Dan M. Kluger, Stephen Bates et al.