Reconstructing the Hubble parameter with future Gravitational Wave missions using Machine Learning. - Purba Mukherjee; Rahul Shah 002; Arko Bhaumik; Supratik Pal (CoRR, 2023)

Neural network reconstruction of cosmology using the Pantheon compilation. - Konstantinos F. Dialektopoulos; Purba Mukherjee; Jackson Levi Said; Jurgen Mifsud (CoRR, 2023)

LADDER: Revisiting the Cosmic Distance Ladder with Deep Learning Approaches and Exploring its Applications. - Rahul Shah 002; Soumadeep Saha; Purba Mukherjee; Utpal Garain; Supratik Pal (CoRR, 2024)

Late-time transition of MB inferred via neural networks. - Purba Mukherjee; Konstantinos F. Dialektopoulos; Jackson Levi Said; Jurgen Mifsud (CoRR, 2024)

Model-independent cosmological inference post DESI DR1 BAO measurements. - Purba Mukherjee; Anjan Ananda Sen (CoRR, 2024)

What can we learn about Reionization astrophysical parameters using Gaussian Process Regression? - Purba Mukherjee; Antara Dey; Supratik Pal (CoRR, 2024)

Model-Agnostic Cosmological Inference with SDSS-IV eBOSS: Simultaneous Probing for Background and Perturbed Universe. - Purba Mukherjee; Anjan Ananda Sen (CoRR, 2024)

Deep Learning Based Recalibration of SDSS and DESI BAO Alleviates Hubble and Clustering Tensions. - Rahul Shah 002; Purba Mukherjee; Soumadeep Saha; Utpal Garain; Supratik Pal (CoRR, 2024)

A New ∼5σ Tension at Characteristic Redshift from DESI-DR1 BAO and DES-SN5YR Observations. - Purba Mukherjee; Anjan Ananda Sen (CoRR, 2025)

Geometric Determinations Of Characteristic Redshifts From DESI-DR2 BAO and DES-SN5YR Observations: Hints For New Expansion Rate Anomalies. - Purba Mukherjee; Anjan Ananda Sen (CoRR, 2025)