Binary Sparse Coding. - Marc Henniges; Gervasio Puertas; Jörg Bornschein; Julian Eggert; Jörg Lücke (LVA/ICA, 2010)

The Maximal Causes of Natural Scenes are Edge Filters. - Gervasio Puertas; Jörg Bornschein; Jörg Lücke (NIPS, 2010)

A Gabor Wavelet Pyramid-Based Object Detection Algorithm. - Yasuomi D. Sato; Jenia Jitsev; Jörg Bornschein; Daniela Pamplona; Christian Keck; Christoph von der Malsburg (ISNN (2), 2011)

Select and Sample - A Model of Efficient Neural Inference and Learning. - Jacquelyn A. Shelton; Jörg Bornschein; Abdul-Saboor Sheikh; Pietro Berkes; Jörg Lücke (NIPS, 2011)

Why MCA? Nonlinear sparse coding with spike-and-slab prior for neurally plausible image encoding. - Jacquelyn A. Shelton; Philip Sterne; Jörg Bornschein; Abdul-Saboor Sheikh; Jörg Lücke (NIPS, 2012)

Are V1 Simple Cells Optimized for Visual Occlusions? A Comparative Study. - Jörg Bornschein; Marc Henniges; Jörg Lücke (PLoS Comput. Biol., 2013)

Large-scale parallelized learning of nonlinear sparse coding models. - Jörg Bornschein (2013)

Towards Biologically Plausible Deep Learning. - Yoshua Bengio; Dong-Hyun Lee; Jörg Bornschein; Zhouhan Lin (CoRR, 2015)

Reweighted Wake-Sleep. - Jörg Bornschein; Yoshua Bengio (ICLR, 2015)

Training opposing directed models using geometric mean matching. - Jörg Bornschein; Samira Shabanian; Asja Fischer; Yoshua Bengio (CoRR, 2015)

Bidirectional Helmholtz Machines. - Jörg Bornschein; Samira Shabanian; Asja Fischer; Yoshua Bengio (ICML, 2016)

Variational Memory Addressing in Generative Models. - Jörg Bornschein; Andriy Mnih; Daniel Zoran; Danilo Jimenez Rezende (NIPS, 2017)

ProSper - A Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions. - Georgios Exarchakis; Jörg Bornschein; Abdul-Saboor Sheikh; Zhenwen Dai; Marc Henniges; Jakob Drefs; Jörg Lücke (CoRR, 2019)

Small Data, Big Decisions: Model Selection in the Small-Data Regime. - Jörg Bornschein; Francesco Visin; Simon Osindero (ICML, 2020)

A study on the plasticity of neural networks. - Tudor Berariu; Wojciech Czarnecki 001; Soham De; Jörg Bornschein; Samuel L. Smith; Razvan Pascanu; Claudia Clopath (CoRR, 2021)

Prequential MDL for Causal Structure Learning with Neural Networks. - Jörg Bornschein; Silvia Chiappa; Alan Malek; Nan Rosemary Ke (CoRR, 2021)

When Does Re-initialization Work? - Sheheryar Zaidi; Tudor Berariu; Hyunjik Kim; Jörg Bornschein; Claudia Clopath; Yee Whye Teh; Razvan Pascanu (ICBINB, 2022)

Learning to Induce Causal Structure. - Nan Rosemary Ke; Silvia Chiappa; Jane Wang 001; Jörg Bornschein; Theophane Weber; Anirudh Goyal; Matthew M. Botvinick; Michael Mozer; Danilo Jimenez Rezende (CoRR, 2022)

NEVIS'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research. - Jörg Bornschein; Alexandre Galashov; Ross Hemsley; Amal Rannen-Triki; Yutian Chen 001; Arslan Chaudhry; Xu Owen He; Arthur Douillard; Massimo Caccia; Qixuang Feng; Jiajun Shen; Sylvestre-Alvise Rebuffi; et al. (CoRR, 2022)

Sequential Learning of Neural Networks for Prequential MDL. - Jörg Bornschein; Yazhe Li; Marcus Hutter (ICLR, 2023)

Learning to Induce Causal Structure. - 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 (ICLR, 2023)

Evaluating Representations with Readout Model Switching. - Yazhe Li; Jörg Bornschein; Marcus Hutter (ICLR, 2023)

DiscoGen: Learning to Discover Gene Regulatory Networks. - 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; et al. (CoRR, 2023)

Towards Robust and Efficient Continual Language Learning. - Adam Fisch; Amal Rannen-Triki; Razvan Pascanu; Jörg Bornschein; Angeliki Lazaridou; Elena Gribovskaya; Marc'Aurelio Ranzato (CoRR, 2023)

Nevis'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research. - Jörg Bornschein; Alexandre Galashov; Ross Hemsley; Amal Rannen-Triki; Yutian Chen 001; Arslan Chaudhry; Xu Owen He; Arthur Douillard; Massimo Caccia; Qixuan Feng; Jiajun Shen; Sylvestre-Alvise Rebuffi; et al. (J. Mach. Learn. Res., 2023)

Bridging the Gap Between Offline and Online Reinforcement Learning Evaluation Methodologies. - Shivakanth Sujit; Pedro H. M. Braga; Jörg Bornschein; Samira Ebrahimi Kahou (Trans. Mach. Learn. Res., 2023)

Kalman Filter for Online Classification of Non-Stationary Data. - Michalis K. Titsias; Alexandre Galashov; Amal Rannen-Triki; Razvan Pascanu; Yee Whye Teh; Jörg Bornschein (ICLR, 2024)

Denoising Autoregressive Representation Learning. - Yazhe Li; Jörg Bornschein; Ting Chen (ICML, 2024)

Imitating Language via Scalable Inverse Reinforcement Learning. - Markus Wulfmeier; Michael Bloesch; Nino Vieillard; Arun Ahuja; Jörg Bornschein; Sandy H. Huang; Artem Sokolov; Matt Barnes 001; Guillaume Desjardins; Alex Bewley; Sarah Bechtle; Jost Tobias Springenberg; et al. (NeurIPS, 2024)

Revisiting Dynamic Evaluation: Online Adaptation for Large Language Models. - Amal Rannen-Triki; Jörg Bornschein; Razvan Pascanu; Marcus Hutter; András György 001; Alexandre Galashov; Yee Whye Teh; Michalis K. Titsias (CoRR, 2024)

Transformers for Supervised Online Continual Learning. - Jörg Bornschein; Yazhe Li; Amal Rannen-Triki (CoRR, 2024)

Predicting from Strings: Language Model Embeddings for Bayesian Optimization. - Tung Nguyen; Qiuyi Zhang 001; Bangding Yang; Chansoo Lee; Jörg Bornschein; Yingjie Miao; Sagi Perel; Yutian Chen 001; Xingyou Song (CoRR, 2024)

How do language models learn facts? Dynamics, curricula and hallucinations. - Nicolas Zucchet; Jörg Bornschein; Stephanie C. Y. Chan; Andrew K. Lampinen; Razvan Pascanu; Soham De (CoRR, 2025)

LLMs are Greedy Agents: Effects of RL Fine-tuning on Decision-Making Abilities. - Thomas Schmied; Jörg Bornschein; Jordi Grau-Moya; Markus Wulfmeier; Razvan Pascanu (CoRR, 2025)

On the generalization of language models from in-context learning and finetuning: a controlled study. - Andrew K. Lampinen; Arslan Chaudhry; Stephanie C. Y. Chan; Cody Wild; Diane Wan; Alex Ku; Jörg Bornschein; Razvan Pascanu; Murray Shanahan; James L. McClelland (CoRR, 2025)