16 citations · 36 across the 10 of their papers we have counts for
10 papers
Selective Memory Retention for Long-Horizon LLM Agents
Pranath Reddy
When does retention matter for memory-augmented LLM agents? We study this with TraceRetain, a lightweight framework for bounded external memory in frozen LLM agents that scores ent…
FlowLensing: Simulating Gravitational Lensing with Flow Matching
Hamees Sayed, Pranath Reddy, Michael W. Toomey +1
Gravitational lensing is one of the most powerful probes of dark matter, yet creating high-fidelity lensed images at scale remains a bottleneck. Existing tools rely on ray-tracing…
Domain adaptation in application to gravitational lens finding
Hanna Parul, Sergei Gleyzer, Pranath Reddy +1
The next decade is expected to see a tenfold increase in the number of strong gravitational lenses, driven by new wide-field imaging surveys. To discover these rare objects, effici…
: A Conditional Diffusion Model for Super-Resolution of Gravitational Lensing Data
Pranath Reddy, Michael W Toomey, Hanna Parul +1
Gravitational lensing data is frequently collected at low resolution due to instrumental limitations and observing conditions. Machine learning-based super-resolution techniques of…
Application of Unsupervised Domain Adaptation for Structural MRI Analysis
Pranath Reddy
The primary goal of this work is to study the effectiveness of an unsupervised domain adaptation approach for various applications such as binary classification and anomaly detecti…
Domain Adaptation for Simulation-Based Dark Matter Searches Using Strong Gravitational Lensing
Stephon Alexander, Sergei Gleyzer, Pranath Reddy +2
Clues to the identity of dark matter have remained surprisingly elusive, given the scope of experimental programs aimed at its identification. While terrestrial experiments may be…
Transient Classification in low SNR Gravitational Wave data using Deep Learning
Rahul Nigam, Amit Mishra, Pranath Reddy
The recent advances in Gravitational-wave astronomy have greatly accelerated the study of Multimessenger astrophysics. There is a need for the development of fast and efficient alg…
Decoding Dark Matter Substructure without Supervision
Stephon Alexander, Sergei Gleyzer, Hanna Parul +4
The identity of dark matter remains one of the most pressing questions in physics today. While many promising dark matter candidates have been put forth over the last half-century,…
CMB-GAN: Fast Simulations of Cosmic Microwave background anisotropy maps using Deep Learning
Amit Mishra, Pranath Reddy, Rahul Nigam
Cosmic Microwave Background (CMB) has been a cornerstone in many cosmology experiments and studies since it was discovered back in 1964. Traditional computational models like CAMB…
Baryon density extraction and isotropy analysis of Cosmic Microwave Background using Deep Learning
Amit Mishra, Pranath Reddy, Rahul Nigam
The discovery of cosmic microwave background (CMB) was a paradigm shift in the study and fundamental understanding of the early universe and also the Big Bang phenomenon. Cosmic mi…