57 citations · 152 across the 6 of their papers we have counts for
11 papers
Exploration in two-stage recommender systems
Jiri Hron, Karl Krauth, Michael I. Jordan +1
Two-stage recommender systems are widely adopted in industry due to their scalability and maintainability. These systems produce recommendations in two steps: (i) multiple nominato…
Infinite attention: NNGP and NTK for deep attention networks
Jiri Hron, Yasaman Bahri, Jascha Sohl-Dickstein +1
There is a growing amount of literature on the relationship between wide neural networks (NNs) and Gaussian processes (GPs), identifying an equivalence between the two for a variet…
Exact posterior distributions of wide Bayesian neural networks
Jiri Hron, Yasaman Bahri, Roman Novak +2
Recent work has shown that the prior over functions induced by a deep Bayesian neural network (BNN) behaves as a Gaussian process (GP) as the width of all layers becomes large. How…
Neural Tangents: Fast and Easy Infinite Neural Networks in Python
Roman Novak, Lechao Xiao, Jiri Hron +4
Neural Tangents is a library designed to enable research into infinite-width neural networks. It provides a high-level API for specifying complex and hierarchical neural network ar…
Orthogonal Estimation of Wasserstein Distances
Mark Rowland, Jiri Hron, Yunhao Tang +3
Wasserstein distances are increasingly used in a wide variety of applications in machine learning. Sliced Wasserstein distances form an important subclass which may be estimated ef…
Successor Uncertainties: Exploration and Uncertainty in Temporal Difference Learning
David Janz, Jiri Hron, Przemysław Mazur +3
Posterior sampling for reinforcement learning (PSRL) is an effective method for balancing exploration and exploitation in reinforcement learning. Randomised value functions (RVF) c…