Concrete Dropout. - Yarin Gal; Jiri Hron; Alex Kendall (NIPS, 2017)

Gaussian Process Behaviour in Wide Deep Neural Networks. - Alexander G. de G. Matthews; Jiri Hron; Mark Rowland 001; Richard E. Turner; Zoubin Ghahramani (ICLR (Poster), 2018)

Variational Bayesian dropout: pitfalls and fixes. - Jiri Hron; Alexander G. de G. Matthews; Zoubin Ghahramani (ICML, 2018)

Successor Uncertainties: exploration and uncertainty in temporal difference learning. - David Janz; Jiri Hron; José Miguel Hernández-Lobato; Katja Hofmann; Sebastian Tschiatschek (CoRR, 2018)

Orthogonal Estimation of Wasserstein Distances. - Mark Rowland 001; Jiri Hron; Yunhao Tang; Krzysztof Choromanski; Tamás Sarlós; Adrian Weller (AISTATS, 2019)

Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes. - Roman Novak; Lechao Xiao; Yasaman Bahri; Jaehoon Lee 001; Greg Yang; Jiri Hron; Daniel A. Abolafia; Jeffrey Pennington; Jascha Sohl-Dickstein (ICLR (Poster), 2019)

Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning. - David Janz; Jiri Hron; Przemyslaw Mazur; Katja Hofmann; José Miguel Hernández-Lobato; Sebastian Tschiatschek (NeurIPS, 2019)

Neural Tangents: Fast and Easy Infinite Neural Networks in Python. - Roman Novak; Lechao Xiao; Jiri Hron; Jaehoon Lee 001; Alexander A. Alemi; Jascha Sohl-Dickstein; Samuel S. Schoenholz (ICLR, 2020)

Infinite attention: NNGP and NTK for deep attention networks. - Jiri Hron; Yasaman Bahri; Jascha Sohl-Dickstein; Roman Novak (ICML, 2020)

Exact posterior distributions of wide Bayesian neural networks. - Jiri Hron; Yasaman Bahri; Roman Novak; Jeffrey Pennington; Jascha Sohl-Dickstein (CoRR, 2020)

Exploration in two-stage recommender systems. - Jiri Hron; Karl Krauth; Michael I. Jordan; Niki Kilbertus (CoRR, 2020)

On Component Interactions in Two-Stage Recommender Systems. - Jiri Hron; Karl Krauth; Michael I. Jordan; Niki Kilbertus (NeurIPS, 2021)

Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling. - Jiri Hron; Roman Novak; Jeffrey Pennington; Jascha Sohl-Dickstein (ICML, 2022)

The Progression of Disparities within the Criminal Justice System: Differential Enforcement and Risk Assessment Instruments. - Miri Zilka; Riccardo Fogliato; Jiri Hron; Bradley Butcher; Carolyn Ashurst; Adrian Weller (FAccT, 2023)

Modeling content creator incentives on algorithm-curated platforms. - Jiri Hron; Karl Krauth; Michael I. Jordan; Niki Kilbertus; Sarah Dean (ICLR, 2023)

Optimising Human-Machine Collaboration for Efficient High-Precision Information Extraction from Text Documents. - Bradley Butcher; Miri Zilka; Darren Cook; Jiri Hron; Adrian Weller (CoRR, 2023)

Beyond Use-Cases: A Participatory Approach to Envisioning Data Science in Law Enforcement. - Caitlin Kearney; Jiri Hron; Helen Kosc; Miri Zilka (FAccT, 2024)

Reimagining AI in Social Work: Practitioner Perspectives on Incorporating Technology in their Practice. - Katie Wassal; Carolyn Ashurst; Jiri Hron; Miri Zilka (CoRR, 2024)

Training Language Models on the Knowledge Graph: Insights on Hallucinations and Their Detectability. - Jiri Hron; Laura Culp; Gamaleldin F. Elsayed; Rosanne Liu; Ben Adlam; Maxwell L. Bileschi; Bernd Bohnet; JD Co-Reyes; Noah Fiedel; C. Daniel Freeman; Izzeddin Gur; Kathleen Kenealy; et al. (CoRR, 2024)

Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models. - Avi Singh; John D. Co-Reyes; Rishabh Agarwal; Ankesh Anand; Piyush Patil; Xavier Garcia; Peter J. Liu; James Harrison; Jaehoon Lee 001; Kelvin Xu; Aaron T. Parisi; Abhishek Kumar; et al. (Trans. Mach. Learn. Res., 2024)