30 Results

Expo Talk Panel
Sun 2:45 End-to-end Bayesian inference workflows in TensorFlow Probability
Mary Ellen Perry
Poster
Tue 7:00 Characterizing Distribution Equivalence and Structure Learning for Cyclic and Acyclic Directed Graphs
AmirEmad Ghassami, Alan Yang, Negar Kiyavash, Kun Zhang
Poster
Tue 7:00 Full Law Identification in Graphical Models of Missing Data: Completeness Results
Razieh Nabi, Rohit Bhattacharya, Ilya Shpitser
Poster
Tue 7:00 Approximation Guarantees of Local Search Algorithms via Localizability of Set Functions
Kaito Fujii
Poster
Tue 8:00 Efficient Identification in Linear Structural Causal Models with Auxiliary Cutsets
Daniel Kumor, Carlos Cinelli, Elias Bareinboim
Poster
Tue 9:00 Learning and Sampling of Atomic Interventions from Observations
Arnab Bhattacharyya, Sutanu Gayen, Saravanan Kandasamy, Ashwin Maran, Vinodchandran N. Variyam
Poster
Tue 9:00 LazyIter: A Fast Algorithm for Counting Markov Equivalent DAGs and Designing Experiments
Ali Teshnizi, Saber Salehkaleybar, Negar Kiyavash
Poster
Tue 10:00 Influence Diagram Bandits: Variational Thompson Sampling for Structured Bandit Problems
Tong Yu, Branislav Kveton, Zheng Wen, Ruiyi Zhang, Ole J. Mengshoel
Poster
Tue 11:00 Causal Structure Discovery from Distributions Arising from Mixtures of DAGs
Basil Saeed, Snigdha Panigrahi, Caroline Uhler
Poster
Tue 12:00 Learning the piece-wise constant graph structure of a varying Ising model
Batiste Le Bars, Pierre Humbert, Argyris Kalogeratos, Nicolas Vayatis
Poster
Tue 18:00 Learning to Learn Kernels with Variational Random Features
Xiantong Zhen, Haoliang Sun, Yingjun Du, Jun Xu, Yilong Yin, Ling Shao, Cees Snoek
Poster
Wed 5:00 Privately Learning Markov Random Fields
Huanyu Zhang, Gautam Kamath, Janardhan Kulkarni, Steven Wu
Poster
Wed 5:00 Fast and Three-rious: Speeding Up Weak Supervision with Triplet Methods
Dan Fu, Mayee Chen, Fred Sala, Sarah Hooper, Kayvon Fatahalian, Christopher Re
Poster
Wed 8:00 Undirected Graphical Models as Approximate Posteriors
Arash Vahdat, Evgeny Andriyash, William Macready
Poster
Wed 8:00 Scaling up Hybrid Probabilistic Inference with Logical and Arithmetic Constraints via Message Passing
Zhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari, Guy Van den Broeck
Poster
Wed 9:00 Fast and Consistent Learning of Hidden Markov Models by Incorporating Non-Consecutive Correlations
Robert Mattila, Cristian R. Rojas, Eric Moulines, Vikram Krishnamurthy, Bo Wahlberg
Poster
Wed 11:00 Deep Gaussian Markov Random Fields
Per Sidén, Fredrik Lindsten
Poster
Wed 12:00 Einsum Networks: Fast and Scalable Learning of Tractable Probabilistic Circuits
Robert Peharz, Steven Lang, Antonio Vergari, Karl Stelzner, Alejandro Molina, Martin Trapp, Guy Van den Broeck, Kristian Kersting, Zoubin Ghahramani
Poster
Wed 13:00 Continuous Time Bayesian Networks with Clocks
Nicolai Engelmann, Dominik Linzner, Heinz Koeppl
Poster
Wed 15:00 LP-SparseMAP: Differentiable Relaxed Optimization for Sparse Structured Prediction
Vlad Niculae, Andre Filipe Torres Martins
Poster
Thu 6:00 Empirical Study of the Benefits of Overparameterization in Learning Latent Variable Models
Rares-Darius Buhai, Yoni Halpern, Yoon Kim, Andrej Risteski, David Sontag
Poster
Thu 6:00 A Flexible Framework for Nonparametric Graphical Modeling that Accommodates Machine Learning
Yunhua Xiang, Noah Simon
Poster
Thu 7:00 Data-Dependent Differentially Private Parameter Learning for Directed Graphical Models
Amrita Roy Chowdhury, Theodoros Rekatsinas, Somesh Jha
Poster
Thu 7:00 Computational and Statistical Tradeoffs in Inferring Combinatorial Structures of Ising Model
Ying Jin, Zhaoran Wang, Junwei Lu
Poster
Thu 9:00 Accelerated Message Passing for Entropy-Regularized MAP Inference
Jonathan Lee, Aldo Pacchiano, Peter Bartlett, Michael Jordan
Poster
Thu 13:00 Amortised Learning by Wake-Sleep
Kevin Wenliang, Theodore Moskovitz, Heishiro Kanagawa, Maneesh Sahani
Workshop
Fri 1:45 Learning with Missing Values
Julie Josse, Jes Frellsen, Pierre-Alexandre Mattei, Gael Varoquaux
Workshop
Fri 2:50 Novel Applications: Embedding a random graph via GNN: Extended mean-field inference theory and RL applications to NP-Hard multi-robot/machine scheduling
Hyunwook Kang
Workshop
Fri 9:10 Invited Talk: Graphical Models based Solutions for Missing Data Problems.
Karthika Mohan
Workshop
Sat 13:30 Invited Talk: Alison Gopnik
Nantas Nardelli