A Recurrent Variational Autoencoder for Human Motion Synthesis. - Ikhsanul Habibie; Daniel Holden; Jonathan Schwarz; Joe Yearsley; Taku Komura (BMVC, 2017)

Progress & Compress: A scalable framework for continual learning. - Jonathan Schwarz; Wojciech Czarnecki 001; Jelena Luketina; Agnieszka Grabska-Barwinska; Yee Whye Teh; Razvan Pascanu; Raia Hadsell (ICML, 2018)

Neural Processes. - Marta Garnelo; Jonathan Schwarz; Dan Rosenbaum; Fabio Viola; Danilo J. Rezende; S. M. Ali Eslami; Yee Whye Teh (CoRR, 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)

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 (ICLR (Poster), 2019)

Attentive Neural Processes. - Hyunjik Kim; Andriy Mnih; Jonathan Schwarz; Marta Garnelo; S. M. Ali Eslami; Dan Rosenbaum; Oriol Vinyals; Yee Whye Teh (ICLR (Poster), 2019)

Experience Replay for Continual Learning. - David Rolnick; Arun Ahuja; Jonathan Schwarz; Timothy P. Lillicrap; Gregory Wayne (NeurIPS, 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)

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)

Characterizing the Role of a Single Coupling Layer in Affine Normalizing Flows. - Felix Draxler; Jonathan Schwarz; Christoph Schnörr; Ullrich Köthe (GCPR, 2020)

Riemannian SOS-Polynomial Normalizing Flows. - Jonathan Schwarz; Felix Draxler; Ullrich Köthe; Christoph Schnörr (GCPR, 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 (ICLR, 2020)

Functional Regularisation for Continual Learning with Gaussian Processes. - Michalis K. Titsias; Jonathan Schwarz; Alexander G. de G. Matthews; Razvan Pascanu; Yee Whye Teh (ICLR, 2020)

Powerpropagation: A sparsity inducing weight reparameterisation. - Jonathan Schwarz; Siddhant M. Jayakumar; Razvan Pascanu; Peter E. Latham; Yee Whye Teh (NeurIPS, 2021)

On the Correspondence Between Replicator Dynamics and Assignment Flows. - Bastian Boll; Jonathan Schwarz; Christoph Schnörr (SSVM, 2021)

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 (Bled eConference, 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)

Meta-Learning Sparse Compression Networks. - Jonathan Schwarz; Yee Whye Teh (Trans. Mach. Learn. Res., 2022)

Modality-Agnostic Variational Compression of Implicit Neural Representations. - Jonathan Richard Schwarz; Jihoon Tack; Yee Whye Teh; Jaeho Lee 001; Jinwoo Shin (ICML, 2023)

Secure Out-of-Distribution Task Generalization with Energy-Based Models. - Shengzhuang Chen; Long-Kai Huang; Jonathan Richard Schwarz; Yilun Du; Ying Wei 001 (NeurIPS, 2023)

Learning Large-scale Neural Fields via Context Pruned Meta-Learning. - Jihoon Tack; Subin Kim 001; Sihyun Yu; Jaeho Lee 001; Jinwoo Shin; Jonathan Richard Schwarz (NeurIPS, 2023)

Modeling Large-Scale Joint Distributions and Inference by Randomized Assignment. - Bastian Boll; Jonathan Schwarz; Daniel Gonzalez-Alvarado; Dmitrij Sitenko; Stefania Petra; Christoph Schnörr (SSVM, 2023)

Quantum State Assignment Flows. - Jonathan Schwarz; Bastian Boll; Daniel Gonzalez-Alvarado; Dmitrij Sitenko; Martin Gärttner; Peter Albers; Christoph Schnörr (SSVM, 2023)

Efficient Meta-Learning via Error-based Context Pruning for Implicit Neural Representations. - Jihoon Tack; Subin Kim 001; Sihyun Yu; Jaeho Lee 001; Jinwoo Shin; Jonathan Richard Schwarz (CoRR, 2023)

Spatial Functa: Scaling Functa to ImageNet Classification and Generation. - Matthias Bauer 001; Emilien Dupont; Andy Brock; Dan Rosenbaum; Jonathan Schwarz; Hyunjik Kim (CoRR, 2023)

Quantum State Assignment Flows. - Jonathan Schwarz; Jonas Cassel; Bastian Boll; Martin Gärttner; Peter Albers; Christoph Schnörr (Entropy, 2023)

C3: High-Performance and Low-Complexity Neural Compression from a Single Image or Video. - Hyunjik Kim; Matthias Bauer 001; Lucas Theis; Jonathan Richard Schwarz; Emilien Dupont (CVPR, 2024)

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 (ECCV (17), 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 001 (ICML, 2024)

CoLoR-Filter: Conditional Loss Reduction Filtering for Targeted Language Model Pre-training. - David Brandfonbrener; Hanlin Zhang 002; Andreas Kirsch 002; Jonathan Richard Schwarz; Sham M. Kakade (NeurIPS, 2024)

Online Adaptation of Language Models with a Memory of Amortized Contexts. - Jihoon Tack; Jaehyung Kim 001; Eric Mitchell; Jinwoo Shin; Yee Whye Teh; Jonathan Richard Schwarz (NeurIPS, 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)

Automatic Expert Discovery in LLM Upcycling via Sparse Interpolated Mixture-of-Experts. - Shengzhuang Chen; Ying Wei 001; Jonathan Richard Schwarz (ACL (1), 2025)

Composable Interventions for Language Models. - Arinbjörn Kolbeinsson; Kyle O'Brien; Tianjin Huang; Shanghua Gao; Shiwei Liu 003; Jonathan Richard Schwarz; Anurag Jayant Vaidya; Faisal Mahmood 001; Marinka Zitnik; Tianlong Chen 001; Thomas Hartvigsen (ICLR, 2025)