Jörg Bornschein

45 papers A* 8Journal 28Unranked 8

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Fine-Tuned In-Context Learners for Efficient Adaptation. CoRR Jörg Bornschein, Clare Lyle, Yazhe Li, Amal Rannen-Triki, Xu Owen He, Razvan Pascanu
2025	J	`jnl`	How do language models learn facts? Dynamics, curricula and hallucinations. CoRR Nicolas Zucchet, Jörg Bornschein, Stephanie C. Y. Chan, Andrew K. Lampinen, Razvan Pascanu, Soham De
2025	J	`jnl`	LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities. CoRR Thomas Schmied, Jörg Bornschein, Jordi Grau-Moya, Markus Wulfmeier, Razvan Pascanu
2025	J	`jnl`	On the generalization of language models from in-context learning and finetuning: a controlled study. CoRR Andrew K. Lampinen, Arslan Chaudhry, Stephanie C. Y. Chan, Cody Wild, Diane Wan, Alex Ku, Jörg Bornschein, Razvan Pascanu, Murray Shanahan, James L. McClelland
2024	A*	`conf`	Denoising Autoregressive Representation Learning. ICML Yazhe Li, Jörg Bornschein, Ting Chen
2024	J	`jnl`	Denoising Autoregressive Representation Learning. CoRR Yazhe Li, Jörg Bornschein, Ting Chen
2024	A*	`conf`	Imitating Language via Scalable Inverse Reinforcement Learning. NeurIPS Markus Wulfmeier, Michael Bloesch, Nino Vieillard, Arun Ahuja, Jörg Bornschein, Sandy H. Huang, Artem Sokolov, Matt Barnes, Guillaume Desjardins, Alex Bewley, Sarah Bechtle, Jost Tobias Springenberg, Nikola Momchev, Olivier Bachem, Matthieu Geist, Martin A. Riedmiller
2024	J	`jnl`	Imitating Language via Scalable Inverse Reinforcement Learning. CoRR Markus Wulfmeier, Michael Bloesch, Nino Vieillard, Arun Ahuja, Jörg Bornschein, Sandy H. Huang, Artem Sokolov, Matt Barnes, Guillaume Desjardins, Alex Bewley, Sarah Maria Elisabeth Bechtle, Jost Tobias Springenberg, Nikola Momchev, Olivier Bachem, Matthieu Geist, Martin A. Riedmiller
2024	A*	`conf`	Kalman Filter for Online Classification of Non-Stationary Data. ICLR Michalis K. Titsias, Alexandre Galashov, Amal Rannen-Triki, Razvan Pascanu, Yee Whye Teh, Jörg Bornschein
2024	J	`jnl`	Predicting from Strings: Language Model Embeddings for Bayesian Optimization. CoRR Tung Nguyen, Qiuyi Zhang, Bangding Yang, Chansoo Lee, Jörg Bornschein, Yingjie Miao, Sagi Perel, Yutian Chen, Xingyou Song
2024	J	`jnl`	Revisiting Dynamic Evaluation: Online Adaptation for Large Language Models. CoRR Amal Rannen-Triki, Jörg Bornschein, Razvan Pascanu, Marcus Hutter, András György, Alexandre Galashov, Yee Whye Teh, Michalis K. Titsias
2024	J	`jnl`	Transformers for Supervised Online Continual Learning. CoRR Jörg Bornschein, Yazhe Li, Amal Rannen-Triki
2023	J	`jnl`	Bridging the Gap Between Offline and Online Reinforcement Learning Evaluation Methodologies. Trans. Mach. Learn. Res. Shivakanth Sujit, Pedro H. M. Braga, Jörg Bornschein, Samira Ebrahimi Kahou
2023	J	`jnl`	DiscoGen: Learning to Discover Gene Regulatory Networks. CoRR Nan Rosemary Ke, Sara-Jane Dunn, Jörg Bornschein, Silvia Chiappa, Mélanie Rey, Jean-Baptiste Lespiau, Albin Cassirer, Jane X. Wang, Theophane Weber, David G. T. Barrett, Matthew M. Botvinick, Anirudh Goyal, Michael Mozer, Danilo J. Rezende
2023	A*	`conf`	Evaluating Representations with Readout Model Switching. ICLR Yazhe Li, Jörg Bornschein, Marcus Hutter
2023	J	`jnl`	Evaluating Representations with Readout Model Switching. CoRR Yazhe Li, Jörg Bornschein, Marcus Hutter
2023	J	`jnl`	Kalman Filter for Online Classification of Non-Stationary Data. CoRR Michalis K. Titsias, Alexandre Galashov, Amal Rannen-Triki, Razvan Pascanu, Yee Whye Teh, Jörg Bornschein
2023	A*	`conf`	Learning to Induce Causal Structure. ICLR Nan Rosemary Ke, Silvia Chiappa, Jane X. Wang, Jörg Bornschein, Anirudh Goyal, Mélanie Rey, Theophane Weber, Matthew M. Botvinick, Michael Curtis Mozer, Danilo Jimenez Rezende
2023	J	`jnl`	Nevis'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research. J. Mach. Learn. Res. Jörg Bornschein, Alexandre Galashov, Ross Hemsley, Amal Rannen-Triki, Yutian Chen, Arslan Chaudhry, Xu Owen He, Arthur Douillard, Massimo Caccia, Qixuan Feng, Jiajun Shen, Sylvestre-Alvise Rebuffi, Kitty Stacpoole, Diego de Las Casas, Will Hawkins, Angeliki Lazaridou, Yee Whye Teh, Andrei A. Rusu, Razvan Pascanu, Marc'Aurelio Ranzato
2023	A*	`conf`	Sequential Learning of Neural Networks for Prequential MDL. ICLR Jörg Bornschein, Yazhe Li, Marcus Hutter
2023	J	`jnl`	Towards Robust and Efficient Continual Language Learning. CoRR Adam Fisch, Amal Rannen-Triki, Razvan Pascanu, Jörg Bornschein, Angeliki Lazaridou, Elena Gribovskaya, Marc'Aurelio Ranzato
2022	J	`jnl`	Bridging the Gap Between Offline and Online Reinforcement Learning Evaluation Methodologies. CoRR Shivakanth Sujit, Pedro H. M. Braga, Jörg Bornschein, Samira Ebrahimi Kahou
2022	J	`jnl`	Learning to Induce Causal Structure. CoRR Nan Rosemary Ke, Silvia Chiappa, Jane Wang, Jörg Bornschein, Theophane Weber, Anirudh Goyal, Matthew M. Botvinick, Michael Mozer, Danilo Jimenez Rezende
2022	J	`jnl`	NEVIS'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research. CoRR Jörg Bornschein, Alexandre Galashov, Ross Hemsley, Amal Rannen-Triki, Yutian Chen, Arslan Chaudhry, Xu Owen He, Arthur Douillard, Massimo Caccia, Qixuang Feng, Jiajun Shen, Sylvestre-Alvise Rebuffi, Kitty Stacpoole, Diego de Las Casas, Will Hawkins, Angeliki Lazaridou, Yee Whye Teh, Andrei A. Rusu, Razvan Pascanu, Marc'Aurelio Ranzato
2022	J	`jnl`	Sequential Learning Of Neural Networks for Prequential MDL. CoRR Jörg Bornschein, Yazhe Li, Marcus Hutter
2022	—	`conf`	When Does Re-initialization Work? ICBINB Sheheryar Zaidi, Tudor Berariu, Hyunjik Kim, Jörg Bornschein, Claudia Clopath, Yee Whye Teh, Razvan Pascanu
2022	J	`jnl`	When Does Re-initialization Work? CoRR Sheheryar Zaidi, Tudor Berariu, Hyunjik Kim, Jörg Bornschein, Claudia Clopath, Yee Whye Teh, Razvan Pascanu
2021	J	`jnl`	A study on the plasticity of neural networks. CoRR Tudor Berariu, Wojciech Czarnecki, Soham De, Jörg Bornschein, Samuel L. Smith, Razvan Pascanu, Claudia Clopath
2021	J	`jnl`	Prequential MDL for Causal Structure Learning with Neural Networks. CoRR Jörg Bornschein, Silvia Chiappa, Alan Malek, Nan Rosemary Ke
2020	A*	`conf`	Small Data, Big Decisions: Model Selection in the Small-Data Regime. ICML Jörg Bornschein, Francesco Visin, Simon Osindero
2020	J	`jnl`	Small Data, Big Decisions: Model Selection in the Small-Data Regime. CoRR Jörg Bornschein, Francesco Visin, Simon Osindero
2019	J	`jnl`	ProSper - A Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions. CoRR Georgios Exarchakis, Jörg Bornschein, Abdul-Saboor Sheikh, Zhenwen Dai, Marc Henniges, Jakob Drefs, Jörg Lücke
2017	—	`conf`	Variational Memory Addressing in Generative Models. NIPS Jörg Bornschein, Andriy Mnih, Daniel Zoran, Danilo Jimenez Rezende
2017	J	`jnl`	Variational Memory Addressing in Generative Models. CoRR Jörg Bornschein, Andriy Mnih, Daniel Zoran, Danilo Jimenez Rezende
2016	A*	`conf`	Bidirectional Helmholtz Machines. ICML Jörg Bornschein, Samira Shabanian, Asja Fischer, Yoshua Bengio
2015	—	`conf`	Reweighted Wake-Sleep. ICLR Jörg Bornschein, Yoshua Bengio
2015	J	`jnl`	Towards Biologically Plausible Deep Learning. CoRR Yoshua Bengio, Dong-hyun Lee, Jörg Bornschein, Zhouhan Lin
2015	J	`jnl`	Training opposing directed models using geometric mean matching. CoRR Jörg Bornschein, Samira Shabanian, Asja Fischer, Yoshua Bengio
2013	J	`jnl`	Are V1 Simple Cells Optimized for Visual Occlusions? A Comparative Study. PLoS Comput. Biol. Jörg Bornschein, Marc Henniges, Jörg Lücke
2013	—	`—`	Large-scale parallelized learning of nonlinear sparse coding models. Jörg Bornschein
2012	—	`conf`	Why MCA? Nonlinear sparse coding with spike-and-slab prior for neurally plausible image encoding. NIPS Jacquelyn A. Shelton, Philip Sterne, Jörg Bornschein, Abdul-Saboor Sheikh, Jörg Lücke
2011	—	`conf`	A Gabor Wavelet Pyramid-Based Object Detection Algorithm. ISNN (2) Yasuomi D. Sato, Jenia Jitsev, Jörg Bornschein, Daniela Pamplona, Christian Keck, Christoph von der Malsburg
2011	—	`conf`	Select and Sample - A Model of Efficient Neural Inference and Learning. NIPS Jacquelyn A. Shelton, Jörg Bornschein, Abdul-Saboor Sheikh, Pietro Berkes, Jörg Lücke
2010	—	`conf`	Binary Sparse Coding. LVA/ICA Marc Henniges, Gervasio Puertas, Jörg Bornschein, Julian Eggert, Jörg Lücke
2010	—	`conf`	The Maximal Causes of Natural Scenes are Edge Filters. NIPS Gervasio Puertas, Jörg Bornschein, Jörg Lücke