Christian A. Naesseth

According to our database, Christian A. Naesseth authored at least 23 papers between 2014 and 2025.

Collaborative distances:

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

2025

Variational Combinatorial Sequential Monte Carlo for Bayesian Phylogenetics in Hyperbolic Space.

Alex Chen, Philippe Chlenski, Kenneth Munyuza, Antonio Khalil Moretti, Christian A. Naesseth, Itsik Pe'er

CoRR, January, 2025

2024

E-Valuating Classifier Two-Sample Tests.

Teodora Pandeva, Tim Bakker, Christian A. Naesseth, Patrick Forré

Trans. Mach. Learn. Res., 2024

Variational Pseudo Marginal Methods for Jet Reconstruction in Particle Physics.

Hanming Yang, Antonio Khalil Moretti, Sebastian Macaluso, Philippe Chlenski, Christian A. Naesseth, Itsik Pe'er

CoRR, 2024

VISA: Variational Inference with Sequential Sample-Average Approximations.

Heiko Zimmermann, Christian Andersson Naesseth, Jan-Willem van de Meent

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Fast yet Safe: Early-Exiting with Risk Control.

Metod Jazbec, Alexander Timans, Tin Hadzi Veljkovic, Kaspar Sakmann, Dan Zhang, Christian Andersson Naesseth, Eric T. Nalisnick

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Variational Flow Matching for Graph Generation.

Floor Eijkelboom, Grigory Bartosh, Christian Andersson Naesseth, Max Welling, Jan-Willem van de Meent

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Equivariant Neural Diffusion for Molecule Generation.

François Cornet, Grigory Bartosh, Mikkel Schmidt, Christian Andersson Naesseth

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modelling.

Grigory Bartosh, Dmitry P. Vetrov, Christian Andersson Naesseth

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Neural Diffusion Models.

Grigory Bartosh, Dmitry P. Vetrov, Christian A. Naesseth

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

A Variational Perspective on Generative Flow Networks.

Heiko Zimmermann, Fredrik Lindsten, Jan-Willem van de Meent, Christian A. Naesseth

Trans. Mach. Learn. Res., 2023

Transport Score Climbing: Variational Inference Using Forward KL and Adaptive Neural Transport.

Liyi Zhang, David M. Blei, Christian A. Naesseth

Trans. Mach. Learn. Res., 2023

Practical and Asymptotically Exact Conditional Sampling in Diffusion Models.

Luhuan Wu, Brian L. Trippe, Christian A. Naesseth, David M. Blei, John P. Cunningham

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

2021

variational combinatorial sequential monte carlo methods for bayesian phylogenetic inference.

Antonio Khalil Moretti, Liyi Zhang, Christian A. Naesseth, Hadiah Venner, David M. Blei, Itsik Pe'er

Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2020

Markovian Score Climbing: Variational Inference with KL(p||q).

Christian A. Naesseth, Fredrik Lindsten, David M. Blei

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

High-Dimensional Filtering Using Nested Sequential Monte Carlo.

Christian A. Naesseth, Fredrik Lindsten, Thomas B. Schön

IEEE Trans. Signal Process., 2019

Elements of Sequential Monte Carlo.

Christian A. Naesseth, Fredrik Lindsten, Thomas B. Schön

Found. Trends Mach. Learn., 2019

2018

Machine learning using approximate inference: Variational and sequential Monte Carlo methods.

Christian Andersson Naesseth

PhD thesis, 2018

Variational Sequential Monte Carlo.

Christian A. Naesseth, Scott W. Linderman, Rajesh Ranganath, David M. Blei

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms.

Christian A. Naesseth, Francisco J. R. Ruiz, Scott W. Linderman, David M. Blei

Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016

Interacting Particle Markov Chain Monte Carlo.

Tom Rainforth, Christian A. Naesseth, Fredrik Lindsten, Brooks Paige, Jan-Willem van de Meent, Arnaud Doucet, Frank D. Wood

Proceedings of the 33nd International Conference on Machine Learning, 2016

2015

Nested Sequential Monte Carlo Methods.

Christian A. Naesseth, Fredrik Lindsten, Thomas B. Schön

Proceedings of the 32nd International Conference on Machine Learning, 2015

2014

Sequential Monte Carlo for Graphical Models.

Christian A. Naesseth, Fredrik Lindsten, Thomas B. Schön

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

Capacity estimation of two-dimensional channels using Sequential Monte Carlo.

Christian A. Naesseth, Fredrik Lindsten, Thomas B. Schön

Proceedings of the 2014 IEEE Information Theory Workshop, 2014