Christian Schröder de Witt

According to our database, Christian Schröder de Witt authored at least 52 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

MALT: Improving Reasoning with Multi-Agent LLM Training.

Sumeet Ramesh Motwani, Chandler Smith, Rocktim Jyoti Das, Markian Rybchuk, Philip H. S. Torr, Ivan Laptev, Fabio Pizzati, Ronald Clark, Christian Schröder de Witt

CoRR, 2024

Delta-Influence: Unlearning Poisons via Influence Functions.

Wenjie Li, Jiawei Li, Christian Schröder de Witt, Ameya Prabhu, Amartya Sanyal

CoRR, 2024

Comparative Global AI Regulation: Policy Perspectives from the EU, China, and the US.

Jon Chun, Christian Schröder de Witt, Katherine Elkins

CoRR, 2024

MAD-Sherlock: Multi-Agent Debates for Out-of-Context Misinformation Detection.

Kumud Lakara, Juil Sock, Christian Rupprecht, Philip Torr, John Collomosse, Christian Schröder de Witt

CoRR, 2024

Efficient Dictionary Learning with Switch Sparse Autoencoders.

Anish Mudide, Joshua Engels, Eric J. Michaud, Max Tegmark, Christian Schröder de Witt

CoRR, 2024

SAGE: Scalable Ground Truth Evaluations for Large Sparse Autoencoders.

Constantin Venhoff, Anisoara Calinescu, Philip Torr, Christian Schröder de Witt

CoRR, 2024

Toward Robust Real-World Audio Deepfake Detection: Closing the Explainability Gap.

Georgia Channing, Juil Sock, Ronald Clark, Philip Torr, Christian Schröder de Witt

CoRR, 2024

Hidden in Plain Text: Emergence & Mitigation of Steganographic Collusion in LLMs.

Yohan Mathew, Ollie Matthews, Robert McCarthy, Joan Velja, Christian Schröder de Witt, Dylan Cope, Nandi Schoots

CoRR, 2024

IDs for AI Systems.

Alan Chan, Noam Kolt, Peter Wills, Usman Anwar, Christian Schröder de Witt, Nitarshan Rajkumar, Lewis Hammond, David Krueger, Lennart Heim, Markus Anderljung

CoRR, 2024

Unelicitable Backdoors in Language Models via Cryptographic Transformer Circuits.

Andis Draguns, Andrew Gritsevskiy, Sumeet Ramesh Motwani, Charlie Rogers-Smith, Jeffrey Ladish, Christian Schröder de Witt

CoRR, 2024

Computing Low-Entropy Couplings for Large-Support Distributions.

Samuel Sokota, Dylan Sam, Christian Schröder de Witt, Spencer Compton, Jakob N. Foerster, J. Zico Kolter

CoRR, 2024

Risks and Opportunities of Open-Source Generative AI.

Francisco Eiras, Aleksandar Petrov, Bertie Vidgen, Christian Schröder de Witt, Fabio Pizzati, Katherine Elkins, Supratik Mukhopadhyay, Adel Bibi, Aaron Purewal, Botos Csaba, Fabro Steibel, Fazel Keshtkar, Fazl Barez, Genevieve Smith, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan Arturo Nolazco, Lori Landay, Matthew Thomas Jackson, Philip H. S. Torr, Trevor Darrell, Yong Suk Lee, Jakob N. Foerster

CoRR, 2024

Near to Mid-term Risks and Opportunities of Open Source Generative AI.

Francisco Eiras, Aleksandar Petrov, Bertie Vidgen, Christian Schröder de Witt, Fabio Pizzati, Katherine Elkins, Supratik Mukhopadhyay, Adel Bibi, Botos Csaba, Fabro Steibel, Fazl Barez, Genevieve Smith, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan A. Nolazco-Flores, Lori Landay, Matthew Thomas Jackson, Paul Röttger, Philip H. S. Torr, Trevor Darrell, Yong Suk Lee, Jakob N. Foerster

CoRR, 2024

Secret Collusion Among Generative AI Agents.

Sumeet Ramesh Motwani, Mikhail Baranchuk, Martin Strohmeier, Vijay Bolina, Philip H. S. Torr, Lewis Hammond, Christian Schröder de Witt

CoRR, 2024

The Danger Of Arrogance: Welfare Equilibra As A Solution To Stackelberg Self-Play In Non-Coincidental Games.

Jake Levi, Chris Lu, Timon Willi, Christian Schröder de Witt, Jakob N. Foerster

CoRR, 2024

Bayesian Exploration Networks.

Mattie Fellows, Brandon Kaplowitz, Christian Schröder de Witt, Shimon Whiteson

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Position: Near to Mid-term Risks and Opportunities of Open-Source Generative AI.

Francisco Eiras, Aleksandar Petrov, Bertie Vidgen, Christian Schröder de Witt, Fabio Pizzati, Katherine Elkins, Supratik Mukhopadhyay, Adel Bibi, Botos Csaba, Fabro Steibel, Fazl Barez, Genevieve Smith, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan A. Nolazco-Flores, Lori Landay, Matthew Thomas Jackson, Paul Röttger, Philip H. S. Torr, Trevor Darrell, Yong Suk Lee, Jakob N. Foerster

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Illusory Attacks: Information-theoretic detectability matters in adversarial attacks.

Tim Franzmeyer, Stephen Marcus McAleer, João F. Henriques, Jakob Nicolaus Foerster, Philip Torr, Adel Bibi, Christian Schröder de Witt

Proceedings of the Twelfth International Conference on Learning Representations, 2024

JaxMARL: Multi-Agent RL Environments and Algorithms in JAX.

Alexander Rutherford, Benjamin Ellis, Matteo Gallici, Jonathan Cook, Andrei Lupu, Garðar Ingvarsson, Timon Willi, Akbir Khan, Christian Schröder de Witt, Alexandra Souly, Saptarashmi Bandyopadhyay, Mikayel Samvelyan, Minqi Jiang, Robert T. Lange, Shimon Whiteson, Bruno Lacerda, Nick Hawes, Tim Rocktäschel, Chris Lu, Jakob N. Foerster

Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

Rethinking Out-of-Distribution Detection for Reinforcement Learning: Advancing Methods for Evaluation and Detection.

Linas Nasvytis, Kai Sandbrink, Jakob N. Foerster, Tim Franzmeyer, Christian Schröder de Witt

Proceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems, 2024

2023

JaxMARL: Multi-Agent RL Environments in JAX.

Alexander Rutherford, Benjamin Ellis, Matteo Gallici, Jonathan Cook, Andrei Lupu, Garðar Ingvarsson, Timon Willi, Akbir Khan, Christian Schröder de Witt, Alexandra Souly, Saptarashmi Bandyopadhyay, Mikayel Samvelyan, Minqi Jiang, Robert Tjarko Lange, Shimon Whiteson, Bruno Lacerda, Nick Hawes, Tim Rocktäschel, Chris Lu, Jakob Nicolaus Foerster

CoRR, 2023

Perfectly Secure Steganography Using Minimum Entropy Coupling.

Christian Schröder de Witt, Samuel Sokota, J. Zico Kolter, Jakob Nicolaus Foerster, Martin Strohmeier

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning.

Yat Long Lo, Christian Schröder de Witt, Samuel Sokota, Jakob Nicolaus Foerster, Shimon Whiteson

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Revealing Robust Oil and Gas Company Macro-Strategies using Deep Multi-Agent Reinforcement Learning.

Dylan R. Radovic, Lucas Kruitwagen, Christian Schröder de Witt, Ben Caldecott, Shane Tomlinson, Mark Workman

CoRR, 2022

Illusionary Attacks on Sequential Decision Makers and Countermeasures.

Tim Franzmeyer, João F. Henriques, Jakob N. Foerster, Philip H. S. Torr, Adel Bibi, Christian Schröder de Witt

CoRR, 2022

Biological Evolution and Genetic Algorithms: Exploring the Space of Abstract Tile Self-Assembly.

Christian Schröder de Witt

CoRR, 2022

(Private)-Retroactive Carbon Pricing [(P)ReCaP]: A Market-based Approach for Climate Finance and Risk Assessment.

Yoshua Bengio, Prateek Gupta, Dylan R. Radovic, Maarten Scholl, Andrew Williams, Christian Schröder de Witt, Tianyu Zhang, Yang Zhang

CoRR, 2022

Equivariant Networks for Zero-Shot Coordination.

Darius Muglich, Christian Schröder de Witt, Elise van der Pol, Shimon Whiteson, Jakob N. Foerster

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Discovered Policy Optimisation.

Chris Lu, Jakub Grudzien Kuba, Alistair Letcher, Luke Metz, Christian Schröder de Witt, Jakob N. Foerster

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Communicating via Markov Decision Processes.

Samuel Sokota, Christian A. Schröder de Witt, Maximilian Igl, Luisa M. Zintgraf, Philip H. S. Torr, Martin Strohmeier, J. Zico Kolter, Shimon Whiteson, Jakob N. Foerster

Proceedings of the International Conference on Machine Learning, 2022

Generalized Beliefs for Cooperative AI.

Darius Muglich, Luisa M. Zintgraf, Christian A. Schröder de Witt, Shimon Whiteson, Jakob N. Foerster

Proceedings of the International Conference on Machine Learning, 2022

Model-Free Opponent Shaping.

Christopher Lu, Timon Willi, Christian A. Schröder de Witt, Jakob N. Foerster

Proceedings of the International Conference on Machine Learning, 2022

Mirror Learning: A Unifying Framework of Policy Optimisation.

Jakub Grudzien Kuba, Christian A. Schröder de Witt, Jakob N. Foerster

Proceedings of the International Conference on Machine Learning, 2022

Amortized Rejection Sampling in Universal Probabilistic Programming.

Saeid Naderiparizi, Adam Scibior, Andreas Munk, Mehrdad Ghadiri, Atilim Gunes Baydin, Bradley J. Gram-Hansen, Christian A. Schröder de Witt, Robert Zinkov, Philip H. S. Torr, Tom Rainforth, Yee Whye Teh, Frank Wood

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Fixed Points in Cyber Space: Rethinking Optimal Evasion Attacks in the Age of AI-NIDS.

Christian Schröder de Witt, Yongchao Huang, Philip H. S. Torr, Martin Strohmeier

CoRR, 2021

Implicit Communication as Minimum Entropy Coupling.

Samuel Sokota, Christian Schröder de Witt, Maximilian Igl, Luisa M. Zintgraf, Philip H. S. Torr, Shimon Whiteson, Jakob N. Foerster

CoRR, 2021

A Self-Supervised Auxiliary Loss for Deep RL in Partially Observable Settings.

Eltayeb Ahmed, Luisa M. Zintgraf, Christian A. Schröder de Witt, Nicolas Usunier

CoRR, 2021

FACMAC: Factored Multi-Agent Centralised Policy Gradients.

Bei Peng, Tabish Rashid, Christian Schröder de Witt, Pierre-Alexandre Kamienny, Philip H. S. Torr, Wendelin Boehmer, Shimon Whiteson

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning.

Shariq Iqbal, Christian A. Schröder de Witt, Bei Peng, Wendelin Boehmer, Shimon Whiteson, Fei Sha

Proceedings of the 38th International Conference on Machine Learning, 2021

RainBench: Towards Data-Driven Global Precipitation Forecasting from Satellite Imagery.

Christian Schröder de Witt, Catherine Tong, Valentina Zantedeschi, Daniele De Martini, Alfredo Kalaitzis, Matthew Chantry, Duncan Watson-Parris, Piotr Bilinski

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning.

Tabish Rashid, Mikayel Samvelyan, Christian Schröder de Witt, Gregory Farquhar, Jakob N. Foerster, Shimon Whiteson

J. Mach. Learn. Res., 2020

RainBench: Towards Global Precipitation Forecasting from Satellite Imagery.

Christian Schröder de Witt, Catherine Tong, Valentina Zantedeschi, Daniele De Martini, Freddie Kalaitzis, Matthew Chantry, Duncan Watson-Parris, Piotr Bilinski

CoRR, 2020

Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?

Christian Schröder de Witt, Tarun Gupta, Denys Makoviichuk, Viktor Makoviychuk, Philip H. S. Torr, Mingfei Sun, Shimon Whiteson

CoRR, 2020

AI-QMIX: Attention and Imagination for Dynamic Multi-Agent Reinforcement Learning.

Shariq Iqbal, Christian A. Schröder de Witt, Bei Peng, Wendelin Böhmer, Shimon Whiteson, Fei Sha

CoRR, 2020

Simulation-Based Inference for Global Health Decisions.

Christian Schröder de Witt, Bradley Gram-Hansen, Nantas Nardelli, Andrew Gambardella, Robert Zinkov, Puneet K. Dokania, N. Siddharth, Ana Belen Espinosa-Gonzalez, Ara Darzi, Philip H. S. Torr, Atilim Günes Baydin

CoRR, 2020

Deep Multi-Agent Reinforcement Learning for Decentralized Continuous Cooperative Control.

Christian Schröder de Witt, Bei Peng, Pierre-Alexandre Kamienny, Philip H. S. Torr, Wendelin Böhmer, Shimon Whiteson

CoRR, 2020

2019

Hijacking Malaria Simulators with Probabilistic Programming.

Bradley Gram-Hansen, Christian Schröder de Witt, Tom Rainforth, Philip H. S. Torr, Yee Whye Teh, Atilim Günes Baydin

CoRR, 2019

Stratospheric Aerosol Injection as a Deep Reinforcement Learning Problem.

Christian Schröder de Witt, Thomas Hornigold

CoRR, 2019

Multi-Agent Common Knowledge Reinforcement Learning.

Christian Schröder de Witt, Jakob N. Foerster, Gregory Farquhar, Philip H. S. Torr, Wendelin Boehmer, Shimon Whiteson

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

The StarCraft Multi-Agent Challenge.

Mikayel Samvelyan, Tabish Rashid, Christian Schröder de Witt, Gregory Farquhar, Nantas Nardelli, Tim G. J. Rudner, Chia-Man Hung, Philip H. S. Torr, Jakob N. Foerster, Shimon Whiteson

Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems, 2019

2018

QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning.

Tabish Rashid, Mikayel Samvelyan, Christian Schröder de Witt, Gregory Farquhar, Jakob N. Foerster, Shimon Whiteson

Proceedings of the 35th International Conference on Machine Learning, 2018

2014

The ZX calculus is incomplete for quantum mechanics.

Christian Schröder de Witt, Vladimir Zamdzhiev

Proceedings of the 11th workshop on Quantum Physics and Logic, 2014