Paul E. Chang

According to our database, Paul E. Chang authored at least 8 papers between 2020 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Amortized Probabilistic Conditioning for Optimization, Simulation and Inference.

Paul E. Chang, Nasrulloh Loka, Daolang Huang, Ulpu Remes, Samuel Kaski, Luigi Acerbi

CoRR, 2024

Function-space Parameterization of Neural Networks for Sequential Learning.

Aidan Scannell, Riccardo Mereu, Paul Edmund Chang, Ella Tamir, Joni Pajarinen, Arno Solin

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Sparse Function-space Representation of Neural Networks.

Aidan Scannell, Riccardo Mereu, Paul E. Chang, Ella Tamir, Joni Pajarinen, Arno Solin

CoRR, 2023

Memory-Based Dual Gaussian Processes for Sequential Learning.

Paul Edmund Chang, Prakhar Verma, S. T. John, Arno Solin, Mohammad Emtiyaz Khan

Proceedings of the International Conference on Machine Learning, 2023

2022

Fantasizing with Dual GPs in Bayesian Optimization and Active Learning.

Paul E. Chang, Prakhar Verma, S. T. John, Victor Picheny, Henry B. Moss, Arno Solin

CoRR, 2022

2021

Dual Parameterization of Sparse Variational Gaussian Processes.

Vincent Adam, Paul E. Chang, Mohammad Emtiyaz Khan, Arno Solin

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

2020

Fast Variational Learning in State-Space Gaussian Process Models.

Paul E. Chang, William J. Wilkinson, Mohammad Emtiyaz Khan, Arno Solin

Proceedings of the 30th IEEE International Workshop on Machine Learning for Signal Processing, 2020

State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian Processes.

William J. Wilkinson, Paul E. Chang, Michael Riis Andersen, Arno Solin

Proceedings of the 37th International Conference on Machine Learning, 2020