activity
20142026
most citedThe CAMELS project: Cosmology and Astrophysics with MachinE Learning Simulations

305 citations · 1.1k across the 49 of their papers we have counts for

collaborators
Showing 2025Show all

12 papers · 1 filter

gr-qc2025

Generating optimal Gravitational-Wave template banks with metric-preserving autoencoders

Giovanni Cabass, Digvijay Wadekar, Matias Zaldarriaga +1

Matched filtering for signal detection in noisy data requires template banks that capture variation in signal waveforms while minimizing computational cost. Dimensionality reductio…

gr-qc2025★ 1 cited

Accurate models for recoil velocity distribution in black hole mergers with comparable to extreme mass-ratios and their astrophysical implications

Tousif Islam, Digvijay Wadekar

Modeling the remnant recoil velocity (kick) distribution from binary black hole mergers is crucial for understanding hierarchical mergers in active galactic nuclei or globular clus…

cs.AI2025★ 1 cited

The Denario project: Deep knowledge AI agents for scientific discovery

Francisco Villaescusa-Navarro, Boris Bolliet, Pablo Villanueva-Domingo +33

We present Denario, an AI multi-agent system designed to serve as a scientific research assistant. Denario can perform many different tasks, such as generating ideas, checking the…

gr-qc2025

Data-driven extraction and phenomenology of eccentric harmonics in eccentric spinning binary black hole mergers

Tousif Islam, Tejaswi Venumadhav, Ajit Kumar Mehta +6

Newtonian and post-Newtonian (PN) calculations indicate that the phenomenology of eccentric binary black hole (BBH) merger waveforms is significantly more complex than that of thei…

gr-qc2025★ 2 cited

Binary black hole population inference combining confident and marginal events from the search pipeline

Ajit Kumar Mehta, Digvijay Wadekar, Isha Anantpurkar +6

We present the population properties of binary black hole mergers identified by the pipeline (which incorporates higher-order modes in the search templates) du…

gr-qc2025

Improving gravitational wave search sensitivity with TIER: Trigger Inference using Extended strain Representation

Digvijay Wadekar, Arush Pimpalkar, Mark Ho-Yeuk Cheung +9

We introduce a machine learning (ML) framework called for improving the sensitivity of gravitational wave search pipelines. Typically, search pipelines only use a s…