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Jörg Bornschein
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2020 – today
- 2024
- [c14]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 - [i19]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 abs/2403.01518 (2024) - [i18]Jörg Bornschein, Yazhe Li, Amal Rannen-Triki:
Transformers for Supervised Online Continual Learning. CoRR abs/2403.01554 (2024) - [i17]Yazhe Li, Jörg Bornschein, Ting Chen:
Denoising Autoregressive Representation Learning. CoRR abs/2403.05196 (2024) - 2023
- [j2]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) - [c13]Jörg Bornschein, Yazhe Li, Marcus Hutter:
Sequential Learning of Neural Networks for Prequential MDL. ICLR 2023 - [c12]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 - [c11]Yazhe Li, Jörg Bornschein, Marcus Hutter:
Evaluating Representations with Readout Model Switching. ICLR 2023 - [i16]Yazhe Li, Jörg Bornschein, Marcus Hutter:
Evaluating Representations with Readout Model Switching. CoRR abs/2302.09579 (2023) - [i15]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 abs/2304.05823 (2023) - [i14]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 abs/2306.08448 (2023) - [i13]Adam Fisch, Amal Rannen-Triki, Razvan Pascanu, Jörg Bornschein, Angeliki Lazaridou, Elena Gribovskaya, Marc'Aurelio Ranzato:
Towards Robust and Efficient Continual Language Learning. CoRR abs/2307.05741 (2023) - 2022
- [c10]Sheheryar Zaidi, Tudor Berariu, Hyunjik Kim, Jörg Bornschein, Claudia Clopath, Yee Whye Teh, Razvan Pascanu:
When Does Re-initialization Work? ICBINB 2022: 12-26 - [i12]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 abs/2204.04875 (2022) - [i11]Sheheryar Zaidi, Tudor Berariu, Hyunjik Kim, Jörg Bornschein, Claudia Clopath
, Yee Whye Teh, Razvan Pascanu:
When Does Re-initialization Work? CoRR abs/2206.10011 (2022) - [i10]Jörg Bornschein, Yazhe Li, Marcus Hutter:
Sequential Learning Of Neural Networks for Prequential MDL. CoRR abs/2210.07931 (2022) - [i9]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 abs/2211.11747 (2022) - [i8]Shivakanth Sujit, Pedro H. M. Braga, Jörg Bornschein, Samira Ebrahimi Kahou:
Bridging the Gap Between Offline and Online Reinforcement Learning Evaluation Methodologies. CoRR abs/2212.08131 (2022) - 2021
- [i7]Tudor Berariu, Wojciech Czarnecki, Soham De, Jörg Bornschein, Samuel L. Smith, Razvan Pascanu, Claudia Clopath:
A study on the plasticity of neural networks. CoRR abs/2106.00042 (2021) - [i6]Jörg Bornschein, Silvia Chiappa, Alan Malek, Nan Rosemary Ke:
Prequential MDL for Causal Structure Learning with Neural Networks. CoRR abs/2107.05481 (2021) - 2020
- [c9]Jörg Bornschein, Francesco Visin, Simon Osindero:
Small Data, Big Decisions: Model Selection in the Small-Data Regime. ICML 2020: 1035-1044 - [i5]Jörg Bornschein, Francesco Visin, Simon Osindero:
Small Data, Big Decisions: Model Selection in the Small-Data Regime. CoRR abs/2009.12583 (2020)
2010 – 2019
- 2019
- [i4]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 abs/1908.06843 (2019) - 2017
- [c8]Jörg Bornschein, Andriy Mnih, Daniel Zoran, Danilo Jimenez Rezende:
Variational Memory Addressing in Generative Models. NIPS 2017: 3920-3929 - [i3]Jörg Bornschein, Andriy Mnih, Daniel Zoran, Danilo Jimenez Rezende:
Variational Memory Addressing in Generative Models. CoRR abs/1709.07116 (2017) - 2016
- [c7]Jörg Bornschein, Samira Shabanian, Asja Fischer, Yoshua Bengio:
Bidirectional Helmholtz Machines. ICML 2016: 2511-2519 - 2015
- [c6]Jörg Bornschein, Yoshua Bengio:
Reweighted Wake-Sleep. ICLR 2015 - [i2]Yoshua Bengio, Dong-Hyun Lee, Jörg Bornschein, Zhouhan Lin:
Towards Biologically Plausible Deep Learning. CoRR abs/1502.04156 (2015) - [i1]Jörg Bornschein, Samira Shabanian, Asja Fischer, Yoshua Bengio:
Training opposing directed models using geometric mean matching. CoRR abs/1506.03877 (2015) - 2013
- [b1]Jörg Bornschein:
Large-scale parallelized learning of nonlinear sparse coding models. Goethe University Frankfurt am Main, 2013, pp. 1-141 - [j1]Jörg Bornschein, Marc Henniges, Jörg Lücke:
Are V1 Simple Cells Optimized for Visual Occlusions? A Comparative Study. PLoS Comput. Biol. 9(6) (2013) - 2012
- [c5]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: 2285-2293 - 2011
- [c4]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: 232-240 - [c3]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: 2618-2626 - 2010
- [c2]Marc Henniges, Gervasio Puertas, Jörg Bornschein, Julian Eggert, Jörg Lücke:
Binary Sparse Coding. LVA/ICA 2010: 450-457 - [c1]Gervasio Puertas, Jörg Bornschein, Jörg Lücke:
The Maximal Causes of Natural Scenes are Edge Filters. NIPS 2010: 1939-1947
Coauthor Index
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last updated on 2024-08-10 00:28 CEST by the dblp team
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