Jiri Hron

Orcid: 0009-0001-3456-7588

According to our database1, Jiri Hron authored at least 17 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Beyond Human Data: Scaling Self-Training for Problem-Solving with Language Models.
CoRR, 2023

Optimising Human-Machine Collaboration for Efficient High-Precision Information Extraction from Text Documents.
CoRR, 2023

Modeling content creator incentives on algorithm-curated platforms.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

The Progression of Disparities within the Criminal Justice System: Differential Enforcement and Risk Assessment Instruments.
Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

2022
Wide Bayesian neural networks have a simple weight posterior: theory and accelerated sampling.
Proceedings of the International Conference on Machine Learning, 2022

2021
On Component Interactions in Two-Stage Recommender Systems.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
Exploration in two-stage recommender systems.
CoRR, 2020

Exact posterior distributions of wide Bayesian neural networks.
CoRR, 2020

Infinite attention: NNGP and NTK for deep attention networks.
Proceedings of the 37th International Conference on Machine Learning, 2020

Neural Tangents: Fast and Easy Infinite Neural Networks in Python.
Proceedings of the 8th International Conference on Learning Representations, 2020

2019
Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Bayesian Deep Convolutional Networks with Many Channels are Gaussian Processes.
Proceedings of the 7th International Conference on Learning Representations, 2019

Orthogonal Estimation of Wasserstein Distances.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
Successor Uncertainties: exploration and uncertainty in temporal difference learning.
CoRR, 2018

Variational Bayesian dropout: pitfalls and fixes.
Proceedings of the 35th International Conference on Machine Learning, 2018

Gaussian Process Behaviour in Wide Deep Neural Networks.
Proceedings of the 6th International Conference on Learning Representations, 2018

2017
Concrete Dropout.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017


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