Vincent Stimper

According to our database, Vincent Stimper authored at least 15 papers between 2019 and 2023.

Collaborative distances:

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

2023

normflows: A PyTorch Package for Normalizing Flows.

Vincent Stimper, David Liu, Andrew Campbell, Vincent Berenz, Lukas Ryll, Bernhard Schölkopf, José Miguel Hernández-Lobato

Dataset, November, 2023

normflows: A PyTorch Package for Normalizing Flows.

Vincent Stimper, David Liu, Andrew Campbell, Vincent Berenz, Lukas Ryll, Bernhard Schölkopf, José Miguel Hernández-Lobato

J. Open Source Softw., July, 2023

normflows: A PyTorch Package for Normalizing Flows.

Vincent Stimper, David Liu, Andrew Campbell, Vincent Berenz, Lukas Ryll, Bernhard Schölkopf, José Miguel Hernández-Lobato

Dataset, July, 2023

normflows: A PyTorch Package for Normalizing Flows.

Vincent Stimper, David Liu, Andrew Campbell, Vincent Berenz, Lukas Ryll, Bernhard Schölkopf, José Miguel Hernández-Lobato

Dataset, June, 2023

normflows: A PyTorch Package for Normalizing Flows.

Vincent Stimper, David Liu, Andrew Campbell, Vincent Berenz, Lukas Ryll, Bernhard Schölkopf, José Miguel Hernández-Lobato

Dataset, June, 2023

A machine learning route between band mapping and band structure.

R. Patrick Xian, Vincent Stimper, Marios Zacharias, Maciej Dendzik, Shuo Dong, Samuel Beaulieu, Bernhard Schölkopf, Martin Wolf, Laurenz Rettig, Christian Carbogno, Stefan Bauer, Ralph Ernstorfer

Nat. Comput. Sci., 2023

SE(3) Equivariant Augmented Coupling Flows.

Laurence I. Midgley, Vincent Stimper, Javier Antorán, Emile Mathieu, Bernhard Schölkopf, José Miguel Hernández-Lobato

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Flow Annealed Importance Sampling Bootstrap.

Laurence Illing Midgley, Vincent Stimper, Gregor N. C. Simm, Bernhard Schölkopf, José Miguel Hernández-Lobato

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Probing the Robustness of Independent Mechanism Analysis for Representation Learning.

Joanna Sliwa, Shubhangi Ghosh, Vincent Stimper, Luigi Gresele, Bernhard Schölkopf

CoRR, 2022

AutoML Two-Sample Test.

Jonas M. Kübler, Vincent Stimper, Simon Buchholz, Krikamol Muandet, Bernhard Schölkopf

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Resampling Base Distributions of Normalizing Flows.

Vincent Stimper, Bernhard Schölkopf, José Miguel Hernández-Lobato

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2022

2021

Bootstrap Your Flow.

Laurence Illing Midgley, Vincent Stimper, Gregor N. C. Simm, José Miguel Hernández-Lobato

CoRR, 2021

Independent mechanism analysis, a new concept?

Luigi Gresele, Julius von Kügelgen, Vincent Stimper, Bernhard Schölkopf, Michel Besserve

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

A Gradient Based Strategy for Hamiltonian Monte Carlo Hyperparameter Optimization.

Andrew Campbell, Wenlong Chen, Vincent Stimper, José Miguel Hernández-Lobato, Yichuan Zhang

Proceedings of the 38th International Conference on Machine Learning, 2021

2019

Multidimensional Contrast Limited Adaptive Histogram Equalization.

Vincent Stimper, Stefan Bauer, Ralph Ernstorfer, Bernhard Schölkopf, Rui Patrick Xian

IEEE Access, 2019