Christian A. Naesseth

Orcid: 0000-0002-2452-8374

Affiliations:
  • Linköping University, Department of Electrical Engineering


According to our database1, Christian A. Naesseth authored at least 21 papers between 2014 and 2024.

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

Timeline

Legend:

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Links

Online presence:

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Bibliography

2024
E-Valuating Classifier Two-Sample Tests.
Trans. Mach. Learn. Res., 2024

Variational Flow Matching for Graph Generation.
CoRR, 2024

Variational Pseudo Marginal Methods for Jet Reconstruction in Particle Physics.
CoRR, 2024

Fast yet Safe: Early-Exiting with Risk Control.
CoRR, 2024

Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modelling.
CoRR, 2024

VISA: Variational Inference with Sequential Sample-Average Approximations.
CoRR, 2024

Neural Diffusion Models.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023
A Variational Perspective on Generative Flow Networks.
Trans. Mach. Learn. Res., 2023

Transport Score Climbing: Variational Inference Using Forward KL and Adaptive Neural Transport.
Trans. Mach. Learn. Res., 2023

Practical and Asymptotically Exact Conditional Sampling in Diffusion Models.
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.
Proceedings of the Thirty-Seventh Conference on Uncertainty in Artificial Intelligence, 2021

2020
Markovian Score Climbing: Variational Inference with KL(p||q).
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.
IEEE Trans. Signal Process., 2019

Elements of Sequential Monte Carlo.
Found. Trends Mach. Learn., 2019

2018
Machine learning using approximate inference: Variational and sequential Monte Carlo methods.
PhD thesis, 2018

Variational Sequential Monte Carlo.
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms.
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017

2016
Interacting Particle Markov Chain Monte Carlo.
Proceedings of the 33nd International Conference on Machine Learning, 2016

2015
Nested Sequential Monte Carlo Methods.
Proceedings of the 32nd International Conference on Machine Learning, 2015

2014
Sequential Monte Carlo for Graphical Models.
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.
Proceedings of the 2014 IEEE Information Theory Workshop, 2014


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