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ORCIDChristian A. Naesseth
Person information
- affiliation: Linköping University, Department of Electrical Engineering
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2020 – today
- 2024
[j5]Teodora Pandeva, Tim Bakker, Christian A. Naesseth, Patrick Forré:
E-Valuating Classifier Two-Sample Tests. Trans. Mach. Learn. Res. 2024 (2024)- [c10]Grigory Bartosh, Dmitry P. Vetrov, Christian A. Naesseth:
Neural Diffusion Models. ICML 2024 - [i14]Heiko Zimmermann, Christian A. Naesseth, Jan-Willem van de Meent:
VISA: Variational Inference with Sequential Sample-Average Approximations. CoRR abs/2403.09429 (2024) - [i13]Grigory Bartosh, Dmitry P. Vetrov, Christian A. Naesseth:
Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modelling. CoRR abs/2404.12940 (2024) - [i12]Metod Jazbec, Alexander Timans, Tin Hadzi Veljkovic, Kaspar Sakmann, Dan Zhang, Christian A. Naesseth, Eric T. Nalisnick:
Fast yet Safe: Early-Exiting with Risk Control. CoRR abs/2405.20915 (2024) - [i11]Hanming Yang, Antonio Khalil Moretti, Sebastian Macaluso, Philippe Chlenski, Christian A. Naesseth, Itsik Pe'er:
Variational Pseudo Marginal Methods for Jet Reconstruction in Particle Physics. CoRR abs/2406.03242 (2024) - [i10]Floor Eijkelboom, Grigory Bartosh, Christian Andersson Naesseth, Max Welling, Jan-Willem van de Meent:
Variational Flow Matching for Graph Generation. CoRR abs/2406.04843 (2024) - 2023
- [j4]Liyi Zhang, David M. Blei, Christian A. Naesseth:
Transport Score Climbing: Variational Inference Using Forward KL and Adaptive Neural Transport. Trans. Mach. Learn. Res. 2023 (2023) - [j3]Heiko Zimmermann, Fredrik Lindsten, Jan-Willem van de Meent, Christian A. Naesseth:
A Variational Perspective on Generative Flow Networks. Trans. Mach. Learn. Res. 2023 (2023) - [c9]Luhuan Wu, Brian L. Trippe, Christian A. Naesseth, David M. Blei, John P. Cunningham:
Practical and Asymptotically Exact Conditional Sampling in Diffusion Models. NeurIPS 2023 - [i9]Luhuan Wu, Brian L. Trippe, Christian A. Naesseth, David M. Blei, John P. Cunningham:
Practical and Asymptotically Exact Conditional Sampling in Diffusion Models. CoRR abs/2306.17775 (2023) - [i8]Grigory Bartosh, Dmitry P. Vetrov, Christian A. Naesseth:
Neural Diffusion Models. CoRR abs/2310.08337 (2023) - 2022
- [i7]Liyi Zhang, Christian A. Naesseth, David M. Blei:
Transport Score Climbing: Variational Inference Using Forward KL and Adaptive Neural Transport. CoRR abs/2202.01841 (2022) - [i6]Heiko Zimmermann, Fredrik Lindsten, Jan-Willem van de Meent, Christian A. Naesseth:
A Variational Perspective on Generative Flow Networks. CoRR abs/2210.07992 (2022) - [i5]Teodora Pandeva, Tim Bakker, Christian A. Naesseth, Patrick Forré:
E-Valuating Classifier Two-Sample Tests. CoRR abs/2210.13027 (2022) - 2021
- [c8]Antonio Khalil Moretti, Liyi Zhang, Christian A. Naesseth, Hadiah Venner, David M. Blei, Itsik Pe'er:
variational combinatorial sequential monte carlo methods for bayesian phylogenetic inference. UAI 2021: 971-981 - [i4]Antonio Khalil Moretti, Liyi Zhang, Christian A. Naesseth, Hadiah Venner, David M. Blei, Itsik Pe'er:
Variational Combinatorial Sequential Monte Carlo Methods for Bayesian Phylogenetic Inference. CoRR abs/2106.00075 (2021) - 2020
- [c7]Christian A. Naesseth, Fredrik Lindsten, David M. Blei:
Markovian Score Climbing: Variational Inference with KL(p||q). NeurIPS 2020 - [i3]Christian A. Naesseth, Fredrik Lindsten, David M. Blei:
Markovian Score Climbing: Variational Inference with KL(p||q). CoRR abs/2003.10374 (2020)
2010 – 2019
- 2019
- [j2]Christian A. Naesseth, Fredrik Lindsten, Thomas B. Schön:
Elements of Sequential Monte Carlo. Found. Trends Mach. Learn. 12(3): 307-392 (2019) - [j1]Christian A. Naesseth
, Fredrik Lindsten, Thomas B. Schön:
High-Dimensional Filtering Using Nested Sequential Monte Carlo. IEEE Trans. Signal Process. 67(16): 4177-4188 (2019) - [i2]Christian A. Naesseth, Fredrik Lindsten, Thomas B. Schön:
Elements of Sequential Monte Carlo. CoRR abs/1903.04797 (2019) - 2018
- [b1]Christian Andersson Naesseth:
Machine learning using approximate inference: Variational and sequential Monte Carlo methods. Linköping University, Sweden, 2018 - [c6]Christian A. Naesseth, Scott W. Linderman, Rajesh Ranganath, David M. Blei:
Variational Sequential Monte Carlo. AISTATS 2018: 968-977 - 2017
- [c5]Christian A. Naesseth, Francisco J. R. Ruiz, Scott W. Linderman, David M. Blei:
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms. AISTATS 2017: 489-498 - 2016
- [c4]Tom Rainforth, Christian A. Naesseth, Fredrik Lindsten, Brooks Paige, Jan-Willem van de Meent, Arnaud Doucet, Frank D. Wood:
Interacting Particle Markov Chain Monte Carlo. ICML 2016: 2616-2625 - 2015
- [c3]Christian A. Naesseth, Fredrik Lindsten, Thomas B. Schön:
Nested Sequential Monte Carlo Methods. ICML 2015: 1292-1301 - 2014
- [c2]Christian A. Naesseth, Fredrik Lindsten, Thomas B. Schön:
Capacity estimation of two-dimensional channels using Sequential Monte Carlo. ITW 2014: 431-435 - [c1]Christian A. Naesseth, Fredrik Lindsten, Thomas B. Schön:
Sequential Monte Carlo for Graphical Models. NIPS 2014: 1862-1870 - [i1]Christian A. Naesseth, Fredrik Lindsten, Thomas B. Schön:
Capacity estimation of two-dimensional channels using Sequential Monte Carlo. CoRR abs/1405.0102 (2014)
Coauthor Index
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