2019
Velocity debiasing for Hubble constant measurements from standard sirens
S. Mukherjee, G. Lavaux, F. R. Bouchet, J. Jasche, B. D. Wandelt, S. M. Nissanke, F. Leclercq, K. Hotokezaka
arXiv:1909.08627arxiv
Neural physical engines for inferring the halo mass distribution function
T. Charnock, G. Lavaux, B. D. Wandelt, S. Sarma Boruah, J. Jasche, M. J. Hudson
arXiv:1909.06379arxiv
Systematic-free inference of the cosmic matter density field from SDSS3-BOSS data
G. Lavaux, J. Jasche, F. Leclercq
arXiv:1909.06396arxiv
The Likelihood For Large-Scale Structure
G. Cabass, F. Schmidt
arXiv:1909.04022arxiv
Cosmology Inference from Biased Tracers using the EFT-based Likelihood
F. Elsner, F. Schmidt, J. Jasche, G. Lavaux, M. Nguyen
arXiv:1906.07143arxiv
Inferring high redshift large-scale structure dynamics from the Lyman-alpha forest
N. Porqueres, J. Jasche, G. Lavaux, T. Ensslin
arXiv:1907.02973arxiv
A local resolution of the Hubble tension: The impact of screened fifth forces on the cosmic distance ladder
H. Desmond, B. Jain, J. Sakstein
arXiv:1907.03778arxiv
Wiener filtering and pure E/B decomposition of CMB maps with anisotropic correlated noise
D. Kodi Ramanah, G. Lavaux, B. D. Wandelt
arXiv:1906.10704arxiv
Painting halos from cosmic density fields of dark matter with physically motivated neural networks
D. Kodi Ramanah, T. Charnock, G. Lavaux
PRD 100, 043515; arXiv:1903.10524arxiv
Primordial power spectrum and cosmology from black-box galaxy surveys
F. Leclercq, W. Enzi, J. Jasche, A. Heavens
arXiv:1902.10149arxiv
Explicit Bayesian treatment of unknown foreground contaminations in galaxy surveys
N. Porqueres, D. Kodi Ramanah, J. Jasche, G. Lavaux
A&A 624, A115; arXiv:1812.05113arxiv
Cosmological inference from Bayesian forward modelling of deep galaxy redshift surveys
D. Kodi Ramanah, G. Lavaux, J. Jasche, B. D. Wandelt
A&A 621, A69; arXiv:1808.07496arxiv
A rigorous EFT-based forward model for large-scale structure
F. Schmidt, F. Elsner, J. Jasche, N. M. Nguyen, G. Lavaux
JCAP 1, 42; arXiv:1808.02002arxiv
Physical Bayesian modelling of the non-linear matter distribution: new insights into the Nearby Universe
J. Jasche, G. Lavaux
A&A 625, A64; arXiv:1806.11117arxiv
The peculiar velocity field up to z~0.05 by forward-modeling Cosmicflows-3 data
R. Graziani, H. M. Courtois, G. Lavaux, Y. Hoffman, R. B. Tully, Y. Copin, D. Pomarède
MNRAS 488, 5438-5451; arXiv:1901.01818arxiv
2018
Fifth force constraints from galaxy warps
H. Desmond, P. Ferreira, G. Lavaux, J. Jasche
Phys. Rev. D 98, 083010; arXiv:1807.11742arxiv
Fifth force constraints from separation of galaxy mass components
H. Desmond, P. Ferreira, G. Lavaux, J. Jasche
Phys. Rev. D 98, 064015; arXiv:1807.01482arxiv
Bayesian optimisation for likelihood-free cosmological inference
F. Leclercq
Phys. Rev. D 98, 063511; arXiv:1805.07152arxiv
The Fifth Force in the Local Cosmic Web
H. Desmond, P. Ferreira, G. Lavaux, J. Jasche
Mon. Not. Roy. Astro. Soc. L 483, L64-L68; arXiv:1802.07206arxiv
The primordial magnetic field in our cosmic backyard
S. Hutschenreuter, S. Dorn, J. Jasche, F. Vazza, D. Paoletti, G. Lavaux, T. A. Enßlin
CQG 35, 154001; arXiv:1803.02629arxiv
Automatic physical inference with information maximising neural networks
T. Charnock, G. Lavaux, B. D. Wandelt
Phys. Rev. D 97, 083004; arXiv:1802.03537arxiv
Optimal and fast E/B separation with a dual messenger field
D. Kodi Ramanah, G. Lavaux, B. D. Wandelt
MNRAS 476, 2825-2834; arXiv:1801.05358arxiv
Imprints of the large-scale structure on AGN formation and evolution
N. Porqueres, J. Jasche, T. Ensslin, G. Lavaux
A&A 612, A31; arXiv:1710.07641arxiv
Reconstructing the gravitational field of the local universe
H. Desmond, P. G. Ferreira, G. Lavaux, J. Jasche
MNRAS 474, 3152-3161; arXiv:1705.02420arxiv
2017
Bayesian power-spectrum inference with foreground and target contamination treatment
J. Jasche, G. Lavaux
A&A 606, A37; arXiv:1706.08971arxiv
Wiener filter reloaded: fast signal reconstruction without preconditioning
D. Kodi Ramanah, G. Lavaux, B. D. Wandelt
MNRAS 468, 1782-1793; arXiv:1702.08852arxiv
The phase-space structure of nearby dark matter as constrained by the SDSS
F. Leclercq, J. Jasche, G. Lavaux, B. Wandelt, W. Percival
JCAP 6, 49; arXiv:1601.00093arxiv
2016
Comparing cosmic web classifiers using information theory
F. Leclercq, G. Lavaux, J. Jasche, B. Wandelt
JCAP 8, 27; arXiv:1606.06758arxiv
Bayesian 3d velocity field reconstruction with VIRBIuS
G. Lavaux
MNRAS 457, 172-197; arXiv:1512.04534arxiv
Unmasking the Masked Universe: the 2M++ catalogue through Bayesian eyes
G. Lavaux, J. Jasche
MNRAS 455, 3169-3179; arXiv:1509.05040arxiv
Halo detection via large-scale Bayesian inference
A. I. Merson, J. Jasche, F. B. Abdalla, O. Lahav, B. D. Wandelt, H. D. Jones, M. Colless
MNRAS 460, 1340-1355; arXiv:1505.03528arxiv
2015
Cosmic web-type classification using decision theory
F. Leclercq, J. Jasche, B. Wandelt
A&A Letters 576, L17; arXiv:1503.00730arxiv
Bayesian analysis of the dynamic cosmic web in the SDSS galaxy survey
F. Leclercq, J. Jasche, B. Wandelt
JCAP 6, 15; arXiv:1502.02690arxiv
Dark matter voids in the SDSS galaxy survey
F. Leclercq, J. Jasche, P. M. Sutter, N. Hamaus, B. Wandelt
JCAP 3, 47; arXiv:1410.0355arxiv
Past and present cosmic structure in the SDSS DR7 main sample
J. Jasche, F. Leclercq, B. D. Wandelt
JCAP 1, 36; arXiv:1409.6308arxiv
Matrix-free Large Scale Bayesian inference in cosmology
J. Jasche, G. Lavaux
MNRAS 447, 1204-1212; arXiv:1402.1763arxiv
2013
Methods for Bayesian power spectrum inference with galaxy surveys
J. Jasche, B. D. Wandelt
ApJ 779, 15; arXiv:1306.1821arxiv
Bayesian physical reconstruction of initial conditions from large scale structure surveys
J. Jasche, B. D. Wandelt
MNRAS 432, 894-913; arXiv:1203.3639arxiv
2012
Bayesian inference from photometric redshift surveys
J. Jasche, B. D. Wandelt
MNRAS 425, 1042-1056; arXiv:1106.2757arxiv
2010
Bayesian power-spectrum inference for Large Scale Structure data
J. Jasche, F. S. Kitaura, B. D. Wandelt, T. A. Enßlin
MNRAS 406, 60-85; arXiv:0911.2493arxiv