Jörg Bornschein

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 26

Top Venues

CoRR

ICLR

ICML

NIPS

Goethe University Frankfurt am Main (PHD)

Education History

Goethe University Frankfurt am Main

PHD

Publications

Yazhe Li, Jörg Bornschein, Ting Chen
Denoising Autoregressive Representation Learning. CoRR (2024)
Michalis K. Titsias, Alexandre Galashov, Amal Rannen-Triki, Razvan Pascanu, Yee Whye Teh, Jörg Bornschein
Kalman Filter for Online Classification of Non-Stationary Data. ICLR (2024)
Amal Rannen-Triki, Jörg Bornschein, Razvan Pascanu, Marcus Hutter, András György, Alexandre Galashov, Yee Whye Teh, Michalis K. Titsias
Revisiting Dynamic Evaluation: Online Adaptation for Large Language Models. CoRR (2024)
Jörg Bornschein, Yazhe Li, Amal Rannen-Triki
Transformers for Supervised Online Continual Learning. CoRR (2024)
Yazhe Li, Jörg Bornschein, Marcus Hutter
Evaluating Representations with Readout Model Switching. CoRR (2023)
Yazhe Li, Jörg Bornschein, Marcus Hutter
Evaluating Representations with Readout Model Switching. ICLR (2023)
Adam Fisch, Amal Rannen-Triki, Razvan Pascanu, Jörg Bornschein, Angeliki Lazaridou, Elena Gribovskaya, Marc'Aurelio Ranzato
Towards Robust and Efficient Continual Language Learning. CoRR (2023)
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
Learning to Induce Causal Structure. ICLR (2023)
Michalis K. Titsias, Alexandre Galashov, Amal Rannen-Triki, Razvan Pascanu, Yee Whye Teh, Jörg Bornschein
Kalman Filter for Online Classification of Non-Stationary Data. CoRR (2023)
Shivakanth Sujit, Pedro H. M. Braga, Jörg Bornschein, Samira Ebrahimi Kahou
Bridging the Gap Between Offline and Online Reinforcement Learning Evaluation Methodologies. Trans. Mach. Learn. Res. 2023 (2023)
Jörg Bornschein, Yazhe Li, Marcus Hutter
Sequential Learning of Neural Networks for Prequential MDL. ICLR (2023)
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
DiscoGen: Learning to Discover Gene Regulatory Networks. CoRR (2023)
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
NEVIS'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research. CoRR (2022)
Jörg Bornschein, Yazhe Li, Marcus Hutter
Sequential Learning Of Neural Networks for Prequential MDL. CoRR (2022)
Sheheryar Zaidi, Tudor Berariu, Hyunjik Kim, Jörg Bornschein, Claudia Clopath, Yee Whye Teh, Razvan Pascanu
When Does Re-initialization Work? CoRR (2022)
Nan Rosemary Ke, Silvia Chiappa, Jane Wang, Jörg Bornschein, Theophane Weber, Anirudh Goyal, Matthew M. Botvinick, Michael Mozer, Danilo Jimenez Rezende
Learning to Induce Causal Structure. CoRR (2022)
Shivakanth Sujit, Pedro H. M. Braga, Jörg Bornschein, Samira Ebrahimi Kahou
Bridging the Gap Between Offline and Online Reinforcement Learning Evaluation Methodologies. CoRR (2022)
Sheheryar Zaidi, Tudor Berariu, Hyunjik Kim, Jörg Bornschein, Claudia Clopath, Yee Whye Teh, Razvan Pascanu
When Does Re-initialization Work? ICBINB (2022)
Jörg Bornschein, Silvia Chiappa, Alan Malek, Nan Rosemary Ke
Prequential MDL for Causal Structure Learning with Neural Networks. CoRR (2021)
Tudor Berariu, Wojciech Czarnecki, Soham De, Jörg Bornschein, Samuel L. Smith, Razvan Pascanu, Claudia Clopath
A study on the plasticity of neural networks. CoRR (2021)
Jörg Bornschein, Francesco Visin, Simon Osindero
Small Data, Big Decisions: Model Selection in the Small-Data Regime. CoRR (2020)
Jörg Bornschein, Francesco Visin, Simon Osindero
Small Data, Big Decisions: Model Selection in the Small-Data Regime. ICML (2020)
Georgios Exarchakis, Jörg Bornschein, Abdul-Saboor Sheikh, Zhenwen Dai, Marc Henniges, Jakob Drefs, Jörg Lücke
ProSper - A Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions. CoRR (2019)
Jörg Bornschein, Andriy Mnih, Daniel Zoran, Danilo Jimenez Rezende
Variational Memory Addressing in Generative Models. NIPS (2017)
Jörg Bornschein, Andriy Mnih, Daniel Zoran, Danilo Jimenez Rezende
Variational Memory Addressing in Generative Models. CoRR (2017)
Jörg Bornschein, Samira Shabanian, Asja Fischer, Yoshua Bengio
Bidirectional Helmholtz Machines. ICML (2016)
Yoshua Bengio, Dong-Hyun Lee, Jörg Bornschein, Zhouhan Lin
Towards Biologically Plausible Deep Learning. CoRR (2015)
Jörg Bornschein, Yoshua Bengio
Reweighted Wake-Sleep. ICLR (2015)
Jörg Bornschein, Samira Shabanian, Asja Fischer, Yoshua Bengio
Training opposing directed models using geometric mean matching. CoRR (2015)
Jörg Bornschein, Marc Henniges, Jörg Lücke
Are V1 Simple Cells Optimized for Visual Occlusions? A Comparative Study. PLoS Comput. Biol. 9 (6) (2013)
Jacquelyn A. Shelton, Philip Sterne, Jörg Bornschein, Abdul-Saboor Sheikh, Jörg Lücke
Why MCA? Nonlinear sparse coding with spike-and-slab prior for neurally plausible image encoding. NIPS (2012)
Yasuomi D. Sato, Jenia Jitsev, Jörg Bornschein, Daniela Pamplona, Christian Keck, Christoph von der Malsburg
A Gabor Wavelet Pyramid-Based Object Detection Algorithm. ISNN (2) (2011)
Jacquelyn A. Shelton, Jörg Bornschein, Abdul-Saboor Sheikh, Pietro Berkes, Jörg Lücke
Select and Sample - A Model of Efficient Neural Inference and Learning. NIPS (2011)
Gervasio Puertas, Jörg Bornschein, Jörg Lücke
The Maximal Causes of Natural Scenes are Edge Filters. NIPS (2010)
Marc Henniges, Gervasio Puertas, Jörg Bornschein, Julian Eggert, Jörg Lücke
Binary Sparse Coding. LVA/ICA (2010)

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Publication Activity (10 Years)

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Jörg Bornschein