Below is a preliminary schedule of the workshop
Saturday 3rd December 2022
9:00 - 9:05 Welcome and Introduction
9:05 - 9:35 Towards Markov Properties for Continuous-Time Dynamical Systems - Joris Mooij
9:35 - 10:05 Causal and Graphical Models for Continuous-Time Event Data - Vanessa Didelez
10:05 - 10:30 Coffee Break
10:30 - 11:00 Dynamic Causal Modelling - Karl Friston
11:00 - 11:30 Causal Feature Selection in Time-Series Data - Atalanti Mastakouri
11:30 - 12:30 Poster Session #1
12:30 - 14:00 Lunch Break
14:00 - 14:30 Signature Kernel Methods - Cristopher Salvi
14:30 - 15:00 Causal Discovery from Nonstationary Time Series - Biwei Huang
15:00 - 15:30 Coffee Break
15:30 - 16:20 Spotlight Talks
16:20 - 16:55 Poster Session #2
16:55 - 17:00 Wrap Up
Registration To attend our workshop, NeurIPS 2022 workshop registration is required. All invited and contributed talks will be live-streamed and will be accessible via the virtual pass.
Poster Sessions All accepted papers will be presented as a poster at the workshop. The poster sessions will be mostly in-person. A few posters might be presented virtually via zoom break-out rooms. In-person poster presenters need to bring their printed posters at the workshop, more information on the posters format and printing locations in New Orleans can be found here.
Quantifying Causal Contribution in Rare Event Data
Ali Caner Turkmen, Dominik Janzing, Oleksandr Shchur, Lenon Minorics, Laurent Callot
Kseniya Solovyeva, David Danks, Mohammadsajad Abavisani, Sergey Plis
Steffen Ridderbusch, Sina Ober-Blöbaum, Paul James Goulart
Petri Nets Enable Causal Reasoning in Dynamical Systems
Ritwik Anand, Jeremy D Zucker, Vartika Tewari, Karen Sachs, Olga Vitek
On the Complexity of Counterfactual Reasoning
Yunqiu Han, Yizuo Chen, Adnan Darwiche
Time Series Causal Link Estimation under Hidden Confounding using Knockoff Interventions
Violeta-Teodora Trifunov, Maha Shadaydeh, Joachim Denzler
Provably Efficient Causal Model-Based Reinforcement Learning for Environment-Agnostic Generalization
Mirco Mutti, Riccardo De Santi, Emanuele Rossi, Juan Felipe Calderon, Michael M. Bronstein, Marcello Restelli
Alexander Tong, Lazar Atanackovic, Jason Hartford, Yoshua Bengio
Felix Yuran Zhou, Roshan Ravishankar
Ilze Amanda Auzina, Cagatay Yildiz, Efstratios Gavves
Causal Discovery in Time Series Data Using Causally Invariant Locally Linear Models (Virtual)
Alexander Mey
Estimating the mechanisms underlying transient dynamics based on peri-event data (Virtual)
Kaidi Shao, Nikos K. Logothetis, Michel Besserve
Jiayao Zhang, Youngsuk Park, Danielle C. Maddix, Dan Roth, Bernie Wang
Learning Heterogeneous Interaction Strengths by Trajectory Prediction with Graph Neural Network
Seungwoong Ha, Hawoong Jeong
A Balanced Design of Time Series Experiments
Tu Ni, Iavor Bojinov, Jinglong Zhao
GRACE-C: Generalized Rate Agnostic Causal Estimation via Constraints
Mohammadsajad Abavisani, David Danks, Vince Calhoun, Sergey Plis
Causal Inference out of Control: Identifying the Steerability of Consumption
Gary Cheng, Moritz Hardt, Celestine Mendler-Dünner
Evaluating vaccine allocation strategies using simulation-assisted causal modelling
Armin Kekić, Jonas Dehning, Luigi Gresele, Julius von Kügelgen, Viola Priesemann, Bernhard Schölkopf
Online Learning of Optimal Control Signals in Stochastic Linear Dynamical Systems
Mohamad Kazem Shirani Faradonbeh
Learning Dynamics and Structure of Complex Systems Using Graph Neural Networks
Zhe Li, Andreas S. Tolias, Xaq Pitkow
Causal Discovery in Time Series Data Using Causally Invariant Locally Linear Models (Virtual)
Alexander Mey
Estimating the mechanisms underlying transient dynamics based on peri-event data (Virtual)
Kaidi Shao, Nikos K. Logothetis, Michel Besserve
All CDS participants are expected to abide by the NeurIPS2022 Code of Conduct