Everything has to end. Many exciting talks and discussions how to extract maximum information about #cosmology from #galaxy-surveys and realise the promise of full #field-level-inference during our workshop @esivienna.bsky.social .... videos here (more to come): www.youtube.com/playlist?lis...
September 26, 2025 at 4:48 PM
Everything has to end. Many exciting talks and discussions how to extract maximum information about #cosmology from #galaxy-surveys and realise the promise of full #field-level-inference during our workshop @esivienna.bsky.social .... videos here (more to come): www.youtube.com/playlist?lis...
Differentiable Fuzzy Cosmic-Web for Field Level Inference P. Rossell\'o, F. -S. Kitaura, D. Forero-S\'anchez, F. Sinigaglia, G. Favole https:// arxiv.org/abs/2506.03969 https:// arxiv.org/pdf/2506.03969 https:// arxiv.org/html/2506.03969 arXiv:2506.039...
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Origin
mastoxiv.page
June 5, 2025 at 7:29 AM
Euclid: Field-level inference of primordial non-Gaussianity and cosmic initial conditions. A. Andrews (1 and 2) et. al. https://arxiv.org/abs/2412.11945
December 17, 2024 at 5:12 AM
Euclid: Field-level inference of primordial non-Gaussianity and cosmic initial conditions. A. Andrews (1 and 2) et. al. https://arxiv.org/abs/2412.11945
Cosmology inference with perturbative forward modeling at the field level: a comparison with joint power spectrum and bispectrum analyses. Kazuyuki Akitsu et. al. https://arxiv.org/abs/2509.09673
September 25, 2025 at 4:30 AM
Cosmology inference with perturbative forward modeling at the field level: a comparison with joint power spectrum and bispectrum analyses. Kazuyuki Akitsu et. al. https://arxiv.org/abs/2509.09673
Ivana Babi\'c, Fabian Schmidt, Beatriz Tucci: Forward vs Backward: Improving BAO Constraints with Field-Level Inference https://arxiv.org/abs/2505.13588 https://arxiv.org/pdf/2505.13588 https://arxiv.org/html/2505.13588
May 21, 2025 at 6:06 AM
Ivana Babi\'c, Fabian Schmidt, Beatriz Tucci: Forward vs Backward: Improving BAO Constraints with Field-Level Inference https://arxiv.org/abs/2505.13588 https://arxiv.org/pdf/2505.13588 https://arxiv.org/html/2505.13588
On the Connection between Field-Level Inference and $n$-point Correlation Functions
https://arxiv.org/pdf/2504.15351
Fabian Schmidt.
https://arxiv.org/pdf/2504.15351
Fabian Schmidt.
https://arxiv.org/abs/2504.15351
arXiv abstract link
arxiv.org
April 23, 2025 at 4:32 AM
On the Connection between Field-Level Inference and $n$-point Correlation Functions
https://arxiv.org/pdf/2504.15351
Fabian Schmidt.
https://arxiv.org/pdf/2504.15351
Fabian Schmidt.
Cosmology inference with perturbative forward modeling at the field level: a comparison with joint power spectrum and bispectrum analyses
https://arxiv.org/pdf/2509.09673
Kazuyuki Akitsu, Marko Simonović, Shi-Fan Chen, Giovanni Cabass, Matias Zaldarriaga.
https://arxiv.org/pdf/2509.09673
Kazuyuki Akitsu, Marko Simonović, Shi-Fan Chen, Giovanni Cabass, Matias Zaldarriaga.
https://arxiv.org/abs/2509.09673
arXiv abstract link
arxiv.org
September 12, 2025 at 4:35 AM
Cosmology inference with perturbative forward modeling at the field level: a comparison with joint power spectrum and bispectrum analyses
https://arxiv.org/pdf/2509.09673
Kazuyuki Akitsu, Marko Simonović, Shi-Fan Chen, Giovanni Cabass, Matias Zaldarriaga.
https://arxiv.org/pdf/2509.09673
Kazuyuki Akitsu, Marko Simonović, Shi-Fan Chen, Giovanni Cabass, Matias Zaldarriaga.
When I see these things I think a lot about the units of analysis and the layers of inference, like, "how much protection can even being in a representative field afford you when the rest of society is stacked so far against you." I think we get so locked on field-level explanations sometimes...
January 12, 2025 at 6:09 PM
When I see these things I think a lot about the units of analysis and the layers of inference, like, "how much protection can even being in a representative field afford you when the rest of society is stacked so far against you." I think we get so locked on field-level explanations sometimes...
comparisons focused on summary statistics, we conduct a comprehensive field-level analysis: evaluating statistical similarity, quantifying implications for cosmological parameter inference, and identifying the regimes in which simulations are [2/8 of https://arxiv.org/abs/2505.13620v1]
May 21, 2025 at 6:07 AM
comparisons focused on summary statistics, we conduct a comprehensive field-level analysis: evaluating statistical similarity, quantifying implications for cosmological parameter inference, and identifying the regimes in which simulations are [2/8 of https://arxiv.org/abs/2505.13620v1]
Flinch: A Differentiable Framework for Field-Level Inference of Cosmological parameters from curved sky data
https://arxiv.org/pdf/2510.26691
Andrea Crespi, Marco Bonici, Arthur Loureiro, Jaime Ruiz-Zapatero, Ivan Sladoljev, Zack Li, Adrian Bayer, Marius Millea, Uroš Seljak.
https://arxiv.org/pdf/2510.26691
Andrea Crespi, Marco Bonici, Arthur Loureiro, Jaime Ruiz-Zapatero, Ivan Sladoljev, Zack Li, Adrian Bayer, Marius Millea, Uroš Seljak.
https://arxiv.org/abs/2510.26691
arXiv abstract link
arxiv.org
October 31, 2025 at 4:35 AM
Flinch: A Differentiable Framework for Field-Level Inference of Cosmological parameters from curved sky data
https://arxiv.org/pdf/2510.26691
Andrea Crespi, Marco Bonici, Arthur Loureiro, Jaime Ruiz-Zapatero, Ivan Sladoljev, Zack Li, Adrian Bayer, Marius Millea, Uroš Seljak.
https://arxiv.org/pdf/2510.26691
Andrea Crespi, Marco Bonici, Arthur Loureiro, Jaime Ruiz-Zapatero, Ivan Sladoljev, Zack Li, Adrian Bayer, Marius Millea, Uroš Seljak.
demonstrate that the methodology approaches the maximum encoded information consistent with Poisson noise. We introduce a Bayesian field-level inference algorithm that leverages the same forward modelling framework used in galaxy, quasar, and Lyman [7/8 of https://arxiv.org/abs/2506.03969v1]
June 5, 2025 at 6:08 AM
demonstrate that the methodology approaches the maximum encoded information consistent with Poisson noise. We introduce a Bayesian field-level inference algorithm that leverages the same forward modelling framework used in galaxy, quasar, and Lyman [7/8 of https://arxiv.org/abs/2506.03969v1]
Equivalence of the field-level inference and conventional analyses on large scales. Francesco Spezzati et. al. https://arxiv.org/abs/2507.05378
July 9, 2025 at 4:53 AM
Equivalence of the field-level inference and conventional analyses on large scales. Francesco Spezzati et. al. https://arxiv.org/abs/2507.05378
smaller cosmological scales. Field-level inference has provided a unique opportunity beyond summary statistics to use all of the information of the galaxy distribution. However, addressing current challenges often [2/8 of https://arxiv.org/abs/2502.13243v1]
February 20, 2025 at 6:06 AM
smaller cosmological scales. Field-level inference has provided a unique opportunity beyond summary statistics to use all of the information of the galaxy distribution. However, addressing current challenges often [2/8 of https://arxiv.org/abs/2502.13243v1]
Fabian Schmidt: On the Connection between Field-Level Inference and $n$-point Correlation Functions https://arxiv.org/abs/2504.15351 https://arxiv.org/pdf/2504.15351 https://arxiv.org/html/2504.15351
April 23, 2025 at 6:07 AM
Fabian Schmidt: On the Connection between Field-Level Inference and $n$-point Correlation Functions https://arxiv.org/abs/2504.15351 https://arxiv.org/pdf/2504.15351 https://arxiv.org/html/2504.15351
Crespi, Bonici, Loureiro, Ruiz-Zapatero, Sladoljev, Li, Bayer, Millea, Seljak: Flinch: A Differentiable Framework for Field-Level Inference of Cosmological parameters from curved sky data https://a...
Origin | Interest | Match
Origin | Interest | Match
Awakari App
awakari.com
October 31, 2025 at 7:24 AM
📣 Evolutionary Scale is supporting the 2025 Protein Engineering Tournament!
Teams get sponsored ESM inference through
@evolutionaryscale.bsky.social's API (Forge), bringing frontier protein AI models into the competition.
Level playing field, real experiments, open results. Register now 👇
Teams get sponsored ESM inference through
@evolutionaryscale.bsky.social's API (Forge), bringing frontier protein AI models into the competition.
Level playing field, real experiments, open results. Register now 👇
August 21, 2025 at 4:13 PM
📣 Evolutionary Scale is supporting the 2025 Protein Engineering Tournament!
Teams get sponsored ESM inference through
@evolutionaryscale.bsky.social's API (Forge), bringing frontier protein AI models into the competition.
Level playing field, real experiments, open results. Register now 👇
Teams get sponsored ESM inference through
@evolutionaryscale.bsky.social's API (Forge), bringing frontier protein AI models into the competition.
Level playing field, real experiments, open results. Register now 👇
arXiv:2504.15351v1 Announce Type: new
Abstract: Bayesian field-level inference of galaxy clustering guarantees optimal extraction of all cosmological information, provided that the data are correctly described by the forward model employed. The [1/6 of https://arxiv.org/abs/2504.15351v1]
Abstract: Bayesian field-level inference of galaxy clustering guarantees optimal extraction of all cosmological information, provided that the data are correctly described by the forward model employed. The [1/6 of https://arxiv.org/abs/2504.15351v1]
April 23, 2025 at 6:07 AM
arXiv:2504.15351v1 Announce Type: new
Abstract: Bayesian field-level inference of galaxy clustering guarantees optimal extraction of all cosmological information, provided that the data are correctly described by the forward model employed. The [1/6 of https://arxiv.org/abs/2504.15351v1]
Abstract: Bayesian field-level inference of galaxy clustering guarantees optimal extraction of all cosmological information, provided that the data are correctly described by the forward model employed. The [1/6 of https://arxiv.org/abs/2504.15351v1]
arXiv:2504.20130v1 Announce Type: new
Abstract: Field-level inference has emerged as a promising framework to fully harness the cosmological information encoded in next-generation galaxy surveys. It involves performing Bayesian inference to jointly [1/7 of https://arxiv.org/abs/2504.20130v1]
Abstract: Field-level inference has emerged as a promising framework to fully harness the cosmological information encoded in next-generation galaxy surveys. It involves performing Bayesian inference to jointly [1/7 of https://arxiv.org/abs/2504.20130v1]
April 30, 2025 at 6:06 AM
arXiv:2504.20130v1 Announce Type: new
Abstract: Field-level inference has emerged as a promising framework to fully harness the cosmological information encoded in next-generation galaxy surveys. It involves performing Bayesian inference to jointly [1/7 of https://arxiv.org/abs/2504.20130v1]
Abstract: Field-level inference has emerged as a promising framework to fully harness the cosmological information encoded in next-generation galaxy surveys. It involves performing Bayesian inference to jointly [1/7 of https://arxiv.org/abs/2504.20130v1]
Differentiable Fuzzy Cosmic-Web for Field Level Inference. P. Rosselló et. al. https://arxiv.org/abs/2506.03969
June 5, 2025 at 5:24 AM
Differentiable Fuzzy Cosmic-Web for Field Level Inference. P. Rosselló et. al. https://arxiv.org/abs/2506.03969
Generalized framework for likelihood-based field-level inference of growth rate from velocity and density fields. Corentin Ravoux et. al. https://arxiv.org/abs/2501.16852
January 29, 2025 at 4:11 AM
Generalized framework for likelihood-based field-level inference of growth rate from velocity and density fields. Corentin Ravoux et. al. https://arxiv.org/abs/2501.16852
gravity using field-level inference. [9/9 of https://arxiv.org/abs/2502.14851v1]
February 21, 2025 at 6:08 AM
gravity using field-level inference. [9/9 of https://arxiv.org/abs/2502.14851v1]
[30/30] 163 Likes, 3 Comments, 2 Posts
2507.06203, cs․CL, 10 Jul 2025
🆕A Survey on Latent Reasoning
Rui-Jie Zhu, Tianhao Peng, Tianhao Cheng, Xingwei Qu, Jinfa Huang, Dawei Zhu, Hao Wang, Kaiwen Xue, Xuanliang Zhang, Yong Shan, Tianle Cai, Taylor Kergan, Assel Kembay, Andrew Smith, Chenghua L...
2507.06203, cs․CL, 10 Jul 2025
🆕A Survey on Latent Reasoning
Rui-Jie Zhu, Tianhao Peng, Tianhao Cheng, Xingwei Qu, Jinfa Huang, Dawei Zhu, Hao Wang, Kaiwen Xue, Xuanliang Zhang, Yong Shan, Tianle Cai, Taylor Kergan, Assel Kembay, Andrew Smith, Chenghua L...
July 14, 2025 at 12:06 AM
[30/30] 163 Likes, 3 Comments, 2 Posts
2507.06203, cs․CL, 10 Jul 2025
🆕A Survey on Latent Reasoning
Rui-Jie Zhu, Tianhao Peng, Tianhao Cheng, Xingwei Qu, Jinfa Huang, Dawei Zhu, Hao Wang, Kaiwen Xue, Xuanliang Zhang, Yong Shan, Tianle Cai, Taylor Kergan, Assel Kembay, Andrew Smith, Chenghua L...
2507.06203, cs․CL, 10 Jul 2025
🆕A Survey on Latent Reasoning
Rui-Jie Zhu, Tianhao Peng, Tianhao Cheng, Xingwei Qu, Jinfa Huang, Dawei Zhu, Hao Wang, Kaiwen Xue, Xuanliang Zhang, Yong Shan, Tianle Cai, Taylor Kergan, Assel Kembay, Andrew Smith, Chenghua L...
LyαNNA II: Field-level inference with noisy Lyα forest spectra. Parth Nayak et. al. https://arxiv.org/abs/2510.19899
October 24, 2025 at 6:30 AM
LyαNNA II: Field-level inference with noisy Lyα forest spectra. Parth Nayak et. al. https://arxiv.org/abs/2510.19899
Bayesian Inference of Initial Conditions from Non-Linear Cosmic Structures using Field-Level Emulators. (replaced) Ludvig Doeser et. al. https://arxiv.org/abs/2312.09271
December 12, 2024 at 4:15 AM
Bayesian Inference of Initial Conditions from Non-Linear Cosmic Structures using Field-Level Emulators. (replaced) Ludvig Doeser et. al. https://arxiv.org/abs/2312.09271