Louis Kirsch - RankMe

37 papers A* 11Journal 23Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Mindstorms in Natural Language-Based Societies of Mind. Comput. Vis. Media Mingchen Zhuge, Haozhe Liu, Francesco Faccio, Dylan R. Ashley, Róbert Csordás, Anand Gopalakrishnan, Abdullah Hamdi, Hasan Abed Al Kader Hammoud, Vincent Herrmann, Kazuki Irie, Louis Kirsch, Bing Li, Guohao Li, Shuming Liu, Jinjie Mai, Piotr Piekos, Aditya A. Ramesh, Imanol Schlag, Weimin Shi, Aleksandar Stanic, Wenyi Wang, Yuhui Wang, Mengmeng Xu, Deng-Ping Fan, Bernard Ghanem, Jürgen Schmidhuber
2025	J	`jnl`	Understanding In-Context Learning of Linear Models in Transformers Through an Adversarial Lens. Trans. Mach. Learn. Res. Usman Anwar, Johannes von Oswald, Louis Kirsch, David Krueger, Spencer Frei
2024	J	`jnl`	Adversarial Robustness of In-Context Learning in Transformers for Linear Regression. CoRR Usman Anwar, Johannes von Oswald, Louis Kirsch, David Krueger, Spencer Frei
2024	J	`jnl`	Automating the Search for Artificial Life with Foundation Models. CoRR Akarsh Kumar, Chris Lu, Louis Kirsch, Yujin Tang, Kenneth O. Stanley, Phillip Isola, David Ha
2024	A*	`conf`	Discovering Temporally-Aware Reinforcement Learning Algorithms. ICLR Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert Tjarko Lange, Shimon Whiteson, Jakob Nicolaus Foerster
2024	J	`jnl`	Discovering Temporally-Aware Reinforcement Learning Algorithms. CoRR Matthew Thomas Jackson, Chris Lu, Louis Kirsch, Robert T. Lange, Shimon Whiteson, Jakob Nicolaus Foerster
2024	A*	`conf`	GPTSwarm: Language Agents as Optimizable Graphs. ICML Mingchen Zhuge, Wenyi Wang, Louis Kirsch, Francesco Faccio, Dmitrii Khizbullin, Jürgen Schmidhuber
2024	J	`jnl`	Language Agents as Optimizable Graphs. CoRR Mingchen Zhuge, Wenyi Wang, Louis Kirsch, Francesco Faccio, Dmitrii Khizbullin, Jürgen Schmidhuber
2024	A*	`conf`	Sequence Compression Speeds Up Credit Assignment in Reinforcement Learning. ICML Aditya A. Ramesh, Kenny John Young, Louis Kirsch, Jürgen Schmidhuber
2024	J	`jnl`	Sequence Compression Speeds Up Credit Assignment in Reinforcement Learning. CoRR Aditya A. Ramesh, Kenny Young, Louis Kirsch, Jürgen Schmidhuber
2023	J	`jnl`	Brain-inspired learning in artificial neural networks: a review. CoRR Samuel Schmidgall, Jascha Achterberg, Thomas Miconi, Louis Kirsch, Rojin Ziaei, S. Pardis Hajiseyedrazi, Jason Eshraghian
2023	A*	`conf`	Goal-Conditioned Generators of Deep Policies. AAAI Francesco Faccio, Vincent Herrmann, Aditya A. Ramesh, Louis Kirsch, Jürgen Schmidhuber
2023	—	`conf`	Learning One Abstract Bit at a Time Through Self-invented Experiments Encoded as Neural Networks. IWAI Vincent Herrmann, Louis Kirsch, Jürgen Schmidhuber
2023	J	`jnl`	Mindstorms in Natural Language-Based Societies of Mind. CoRR Mingchen Zhuge, Haozhe Liu, Francesco Faccio, Dylan R. Ashley, Róbert Csordás, Anand Gopalakrishnan, Abdullah Hamdi, Hasan Abed Al Kader Hammoud, Vincent Herrmann, Kazuki Irie, Louis Kirsch, Bing Li, Guohao Li, Shuming Liu, Jinjie Mai, Piotr Piekos, Aditya A. Ramesh, Imanol Schlag, Weimin Shi, Aleksandar Stanic, Wenyi Wang, Yuhui Wang, Mengmeng Xu, Deng-Ping Fan, Bernard Ghanem, Jürgen Schmidhuber
2023	A*	`conf`	The Benefits of Model-Based Generalization in Reinforcement Learning. ICML Kenny John Young, Aditya A. Ramesh, Louis Kirsch, Jürgen Schmidhuber
2023	J	`jnl`	The Languini Kitchen: Enabling Language Modelling Research at Different Scales of Compute. CoRR Aleksandar Stanic, Dylan R. Ashley, Oleg Serikov, Louis Kirsch, Francesco Faccio, Jürgen Schmidhuber, Thomas Hofmann, Imanol Schlag
2022	J	`jnl`	Eliminating Meta Optimization Through Self-Referential Meta Learning. CoRR Louis Kirsch, Jürgen Schmidhuber
2022	A*	`conf`	Exploring through Random Curiosity with General Value Functions. NeurIPS Aditya A. Ramesh, Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber
2022	J	`jnl`	Exploring through Random Curiosity with General Value Functions. CoRR Aditya A. Ramesh, Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber
2022	J	`jnl`	General-Purpose In-Context Learning by Meta-Learning Transformers. CoRR Louis Kirsch, James Harrison, Jascha Sohl-Dickstein, Luke Metz
2022	J	`jnl`	Goal-Conditioned Generators of Deep Policies. CoRR Francesco Faccio, Vincent Herrmann, Aditya A. Ramesh, Louis Kirsch, Jürgen Schmidhuber
2022	A*	`conf`	Introducing Symmetries to Black Box Meta Reinforcement Learning. AAAI Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt, Abram L. Friesen, Junhyuk Oh, Yutian Chen
2022	J	`jnl`	Learning One Abstract Bit at a Time Through Self-Invented Experiments Encoded as Neural Networks. CoRR Vincent Herrmann, Louis Kirsch, Jürgen Schmidhuber
2022	J	`jnl`	The Benefits of Model-Based Generalization in Reinforcement Learning. CoRR Kenny Young, Aditya A. Ramesh, Louis Kirsch, Jürgen Schmidhuber
2021	J	`jnl`	Introducing Symmetries to Black Box Meta Reinforcement Learning. CoRR Louis Kirsch, Sebastian Flennerhag, Hado van Hasselt, Abram L. Friesen, Junhyuk Oh, Yutian Chen
2021	A*	`conf`	Meta Learning Backpropagation And Improving It. NeurIPS Louis Kirsch, Jürgen Schmidhuber
2021	A*	`conf`	Parameter-Based Value Functions. ICLR Francesco Faccio, Louis Kirsch, Jürgen Schmidhuber
2020	A*	`conf`	Improving Generalization in Meta Reinforcement Learning using Learned Objectives. ICLR Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber
2020	J	`jnl`	Meta Learning Backpropagation And Improving It. CoRR Louis Kirsch, Jürgen Schmidhuber
2019	J	`jnl`	Gaussian Mean Field Regularizes by Limiting Learned Information. CoRR Julius Kunze, Louis Kirsch, Hippolyt Ritter, David Barber
2019	J	`jnl`	Gaussian Mean Field Regularizes by Limiting Learned Information. Entropy Julius Kunze, Louis Kirsch, Hippolyt Ritter, David Barber
2019	J	`jnl`	Improving Generalization in Meta Reinforcement Learning using Learned Objectives. CoRR Louis Kirsch, Sjoerd van Steenkiste, Jürgen Schmidhuber
2018	A*	`conf`	Modular Networks: Learning to Decompose Neural Computation. NeurIPS Louis Kirsch, Julius Kunze, David Barber
2018	J	`jnl`	Modular Networks: Learning to Decompose Neural Computation. CoRR Louis Kirsch, Julius Kunze, David Barber
2017	—	`conf`	Framework for Exploring and Understanding Multivariate Correlations. ECML/PKDD (3) Louis Kirsch, Niklas Riekenbrauck, Daniel Thevessen, Marcus Pappik, Axel Stebner, Julius Kunze, Alexander Meissner, Arvind Kumar Shekar, Emmanuel Müller
2017	—	`conf`	Transfer Learning for Speech Recognition on a Budget. Rep4NLP@ACL Julius Kunze, Louis Kirsch, Ilia Kurenkov, Andreas Krug, Jens Johannsmeier, Sebastian Stober
2017	J	`jnl`	Transfer Learning for Speech Recognition on a Budget. CoRR Julius Kunze, Louis Kirsch, Ilia Kurenkov, Andreas Krug, Jens Johannsmeier, Sebastian Stober