Poster Sessions
Zurich Pre-NeurIPS 2024 Poster Session
This poster session will be a great opportunity to showcase your research and connect with fellow researchers. Not only will we primarily feature posters of papers accepted to this year’s Conference on Neural Information Processing Systems (NeurIPS) 2024, but we also welcome peer-reviewed work from other conferences and workshops, as much as space allows.
Already 10+ registered posters (see below) and 20+ registered attendees: we hope to receive your registration soon!
Event Details:
- 🗓️ Date and Time: Thursday, November 28, from 1:00 PM to 4:00 PM
- 📍Location: ETH AI Center, Andreasstrasse 5, 8092 Zürich – OAT X 11 (Floor 19) external page https://maps.app.goo.gl/ToZTBkCorbE638tE8
- 🆕 Stay up to date about changes by registering as attendee or presenter below
Food, snacks, and beverages will be provided at the event, for those registered.
We look forward to seeing you there!
👥 Attend and/or Present
Please register through the following form if you plan to attend or if you would like to present your poster, at your earliest convenience: external page https://forms.gle/LehmG8AaCgyViXVR9
Registered posters include:
- Transition Constrained Bayesian Optimization via Markov Decision Processes
Jose Pablo Folch, Calvin Tsay, Robert M Lee, Behrang Shafei, Weronika Ormaniec, Andreas Krause, Mark van der Wilk, Ruth Misener, Mojmír Mutný - Transductive Active Learning: Theory and Applications
Jonas Hübotter, Bhavya Sukhija, Lenart Treven, Yarden As, Andreas Krause - MultiOOD: Scaling Out-of-Distribution Detection for Multiple Modalities
Hao Dong, Yue Zhao, Eleni Chatzi, Olga Fink
- Confidence Regulation Neurons in Language Models
Alessandro Stolfo, Ben Wu, Wes Gurnee, Yonatan Belinkov, Xingyi Song, Mrinmaya Sachan, Neel Nanda
- Contextual Bilevel Reinforcement Learning for Incentive Alignment
Vinzenz Thoma, Barna Pásztor, Andreas Krause, Giorgia Ramponi, Yifan Hu - Physics-Regularized Multi-Modal Image Assimilation for Brain Tumor Localization
Michal Balcerak, Tamaz Amiranashvili, Andreas Wagner, Jonas Weidner, Petr Karnakov, Johannes C. Paetzold, Ivan Ezhov, Petros Koumoutsakos, Benedikt Wiestler, Bjoern Menze - FUSE: Fast Unified Simulation and Estimation for PDEs
Levi E. Lingsch, Dana Grund, Siddhartha Mishra, Georgios Kissas - Components Beat Patches: Eigenvector Masking from Visual Representation Learning
Alice Bizeul, Thomas M. Sutter, Alain Ryser, Julius von Kugelgen, Bernhard Scholkopf, Julia E. Vogt - An Adversarial Perspective on Machine Unlearning for AI Safety
Jakub Łucki, Boyi Wei, Yangsibo Huang, Peter Henderson, Florian Tramèr, Javier Rando - AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents
Edoardo Debenedetti, Jie Zhang, Mislav Balunović, Luca Beurer-Kellner, Marc Fischer, Florian Tramèr - Poseidon: Efficient Foundation Models for PDEs
Maximilian Herde, Bogdan Raonić, Tobias Rohner, Roger Käppeli, Roberto Molinaro, Emmanuel de Bézenac, Siddhartha Mishra - Implicit Regularization of Sharpness-Aware Minimization for Scale-Invariant Problems
Bingcong Li, Liang Zhang, Niao He - Super Consistency of Neural Network's Landscape and Learning Rate Transfer
Lorenzo Noci, Alexandru Meterez, Thomas Hofmann, Antonio Orvieto - Stepwise Verification and Remediation of Student Reasoning Errors with Large Language Model Tutors
Nico Daheim, Jakub Macina, Manu Kapur, Iryna Gurevych, Mrinmaya Sachan - Variational Best-of-N Alignment
Afra Amini, Tim Vieira, Ryan Cotterell - Preconditioned Crank-Nicolson Algorithms for Wide Bayesian Neural Networks
Lucia Pezzetti, Stefano Favaro, Stefano Peluchetti - Quantifying and Estimating the Predictability Upper Bound of Univariate Numeric Time Series
Jamal Mohammed, Michael H. Böhlen, Sven Helmer - Exploring Human Curiosity and Behavior from Natural Queries
Ahmad Khan, Zhujing Jin, Mrinmaya Sachan
