Jonathan Schwarz

According to our database, Jonathan Schwarz authored at least 31 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Empowering Biomedical Discovery with AI Agents.

Shanghua Gao, Ada Fang, Yepeng Huang, Valentina Giunchiglia, Ayush Noori, Jonathan Richard Schwarz, Yasha Ektefaie, Jovana Kondic, Marinka Zitnik

CoRR, 2024

Unleashing the Power of Meta-tuning for Few-shot Generalization Through Sparse Interpolated Experts.

Shengzhuang Chen, Jihoon Tack, Yunqiao Yang, Yee Whye Teh, Jonathan Richard Schwarz, Ying Wei

CoRR, 2024

Online Adaptation of Language Models with a Memory of Amortized Contexts.

Jihoon Tack, Jaehyung Kim, Eric Mitchell, Jinwoo Shin, Yee Whye Teh, Jonathan Richard Schwarz

CoRR, 2024

2023

Quantum State Assignment Flows.

Jonathan Schwarz, Jonas Cassel, Bastian Boll, Martin Gärttner, Peter Albers, Christoph Schnörr

Entropy, September, 2023

Bad Students Make Great Teachers: Active Learning Accelerates Large-Scale Visual Understanding.

Talfan Evans, Shreya Pathak, Hamza Merzic, Jonathan Schwarz, Ryutaro Tanno, Olivier J. Hénaff

CoRR, 2023

C3: High-performance and low-complexity neural compression from a single image or video.

Hyunjik Kim, Matthias Bauer, Lucas Theis, Jonathan Richard Schwarz, Emilien Dupont

CoRR, 2023

Spatial Functa: Scaling Functa to ImageNet Classification and Generation.

Matthias Bauer, Emilien Dupont, Andy Brock, Dan Rosenbaum, Jonathan Schwarz, Hyunjik Kim

CoRR, 2023

Efficient Meta-Learning via Error-based Context Pruning for Implicit Neural Representations.

Jihoon Tack, Subin Kim, Sihyun Yu, Jaeho Lee, Jinwoo Shin, Jonathan Richard Schwarz

CoRR, 2023

Quantum State Assignment Flows.

Jonathan Schwarz, Bastian Boll, Daniel Gonzalez-Alvarado, Dmitrij Sitenko, Martin Gärttner, Peter Albers, Christoph Schnörr

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2023

Modeling Large-Scale Joint Distributions and Inference by Randomized Assignment.

Bastian Boll, Jonathan Schwarz, Daniel Gonzalez-Alvarado, Dmitrij Sitenko, Stefania Petra, Christoph Schnörr

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2023

Learning Large-scale Neural Fields via Context Pruned Meta-Learning.

Jihoon Tack, Subin Kim, Sihyun Yu, Jaeho Lee, Jinwoo Shin, Jonathan Richard Schwarz

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Secure Out-of-Distribution Task Generalization with Energy-Based Models.

Shengzhuang Chen, Long-Kai Huang, Jonathan Richard Schwarz, Yilun Du, Ying Wei

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Modality-Agnostic Variational Compression of Implicit Neural Representations.

Jonathan Richard Schwarz, Jihoon Tack, Yee Whye Teh, Jaeho Lee, Jinwoo Shin

Proceedings of the International Conference on Machine Learning, 2023

2022

Meta-Learning Sparse Compression Networks.

Jonathan Schwarz, Yee Whye Teh

Trans. Mach. Learn. Res., 2022

Behavior Priors for Efficient Reinforcement Learning.

Dhruva Tirumala, Alexandre Galashov, Hyeonwoo Noh, Leonard Hasenclever, Razvan Pascanu, Jonathan Schwarz, Guillaume Desjardins, Wojciech Marian Czarnecki, Arun Ahuja, Yee Whye Teh, Nicolas Heess

J. Mach. Learn. Res., 2022

Designing Urban Participation Platforms - Model for Goal-oriented Classification of Participation Mechanisms.

Pascal Abel, Ricarda Schlimbach, Valentin Glimmann, Jonathan Schwarz, Martin Simon, Susanne Robra-Bissantz

Proceedings of the 35th Bled eConference - Digital Restructuring and Human (Re)action, June 26, 2022

2021

On the Correspondence Between Replicator Dynamics and Assignment Flows.

Bastian Boll, Jonathan Schwarz, Christoph Schnörr

Proceedings of the Scale Space and Variational Methods in Computer Vision, 2021

Powerpropagation: A sparsity inducing weight reparameterisation.

Jonathan Schwarz, Siddhant M. Jayakumar, Razvan Pascanu, Peter E. Latham, Yee Whye Teh

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Functional Regularisation for Continual Learning with Gaussian Processes.

Michalis K. Titsias, Jonathan Schwarz, Alexander G. de G. Matthews, Razvan Pascanu, Yee Whye Teh

Proceedings of the 8th International Conference on Learning Representations, 2020

Multiplicative Interactions and Where to Find Them.

Siddhant M. Jayakumar, Wojciech M. Czarnecki, Jacob Menick, Jonathan Schwarz, Jack W. Rae, Simon Osindero, Yee Whye Teh, Tim Harley, Razvan Pascanu

Proceedings of the 8th International Conference on Learning Representations, 2020

Riemannian SOS-Polynomial Normalizing Flows.

Jonathan Schwarz, Felix Draxler, Ullrich Köthe, Christoph Schnörr

Proceedings of the Pattern Recognition - 42nd DAGM German Conference, DAGM GCPR 2020, Tübingen, Germany, September 28, 2020

Characterizing the Role of a Single Coupling Layer in Affine Normalizing Flows.

Felix Draxler, Jonathan Schwarz, Christoph Schnörr, Ullrich Köthe

Proceedings of the Pattern Recognition - 42nd DAGM German Conference, DAGM GCPR 2020, Tübingen, Germany, September 28, 2020

2019

Meta-Learning surrogate models for sequential decision making.

Alexandre Galashov, Jonathan Schwarz, Hyunjik Kim, Marta Garnelo, David Saxton, Pushmeet Kohli, S. M. Ali Eslami, Yee Whye Teh

CoRR, 2019

Functional Regularisation for Continual Learning using Gaussian Processes.

Michalis K. Titsias, Jonathan Schwarz, Alexander G. de G. Matthews, Razvan Pascanu, Yee Whye Teh

CoRR, 2019

Experience Replay for Continual Learning.

David Rolnick, Arun Ahuja, Jonathan Schwarz, Timothy P. Lillicrap, Gregory Wayne

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Attentive Neural Processes.

Hyunjik Kim, Andriy Mnih, Jonathan Schwarz, Marta Garnelo, S. M. Ali Eslami, Dan Rosenbaum, Oriol Vinyals, Yee Whye Teh

Proceedings of the 7th International Conference on Learning Representations, 2019

Information asymmetry in KL-regularized RL.

Alexandre Galashov, Siddhant M. Jayakumar, Leonard Hasenclever, Dhruva Tirumala, Jonathan Schwarz, Guillaume Desjardins, Wojciech M. Czarnecki, Yee Whye Teh, Razvan Pascanu, Nicolas Heess

Proceedings of the 7th International Conference on Learning Representations, 2019

2018

The NarrativeQA Reading Comprehension Challenge.

Tomás Kociský, Jonathan Schwarz, Phil Blunsom, Chris Dyer, Karl Moritz Hermann, Gábor Melis, Edward Grefenstette

Trans. Assoc. Comput. Linguistics, 2018

Neural Processes.

Marta Garnelo, Jonathan Schwarz, Dan Rosenbaum, Fabio Viola, Danilo J. Rezende, S. M. Ali Eslami, Yee Whye Teh

CoRR, 2018

Progress & Compress: A scalable framework for continual learning.

Jonathan Schwarz, Wojciech Czarnecki, Jelena Luketina, Agnieszka Grabska-Barwinska, Yee Whye Teh, Razvan Pascanu, Raia Hadsell

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

A Recurrent Variational Autoencoder for Human Motion Synthesis.

Ikhsanul Habibie, Daniel Holden, Jonathan Schwarz, Joe Yearsley, Taku Komura

Proceedings of the British Machine Vision Conference 2017, 2017