Zobrazeno 1 - 10
of 41 309
pro vyhledávání: '"A, Gopalakrishnan"'
We present a self-supervised framework for Cone-Beam Computed Tomography (CBCT) reconstruction by directly optimizing a voxelgrid representation using physics-based differentiable X-ray rendering. Further, we investigate how the different formulation
Externí odkaz:
http://arxiv.org/abs/2411.19224
Deep learning-based models for All-In-One Image Restoration (AIOR) have achieved significant advancements in recent years. However, their practical applicability is limited by poor generalization to samples outside the training distribution. This lim
Externí odkaz:
http://arxiv.org/abs/2411.17687
Autor:
Qu, Yi-Fan, Stefanini, Martino, Shi, Tao, Esslinger, Tilman, Gopalakrishnan, Sarang, Marino, Jamir, Demler, Eugene
Recent experiments with quantum simulators using ultracold atoms and superconducting qubits have demonstrated the potential of controlled dissipation as a versatile tool for realizing correlated many-body states. However, determining the dynamics of
Externí odkaz:
http://arxiv.org/abs/2411.13638
We investigate the thermodynamic limits on scaling fault-tolerant quantum computers due to heating from quantum error correction (QEC). Quantum computers require error correction, which accounts for 99.9% of the qubit demand and generates heat throug
Externí odkaz:
http://arxiv.org/abs/2411.12805
We consider one dimensional many-particle systems that exhibit kinematically protected single-particle excitations over their ground states. We show that momentum and time-resolved 4-point functions of operators that create such excitations diverge l
Externí odkaz:
http://arxiv.org/abs/2411.06167
Autor:
Sengupta, Ayan, Seth, Vaibhav, Pathak, Arinjay, Raman, Natraj, Gopalakrishnan, Sriram, Chakraborty, Tanmoy
Large Language Models (LLMs) are highly resource-intensive to fine-tune due to their enormous size. While low-rank adaptation is a prominent parameter-efficient fine-tuning approach, it suffers from sensitivity to hyperparameter choices, leading to i
Externí odkaz:
http://arxiv.org/abs/2411.04358
We consider measurement-induced phase transitions in monitored quantum circuits with a measurement rate that fluctuates in time. The spatially correlated fluctuations in the measurement rate disrupt the volume-law phase for low measurement rates; at
Externí odkaz:
http://arxiv.org/abs/2411.03442
Autor:
Nguyen, Viet Cuong, Taher, Mohammad, Hong, Dongwan, Possobom, Vinicius Konkolics, Gopalakrishnan, Vibha Thirunellayi, Raj, Ekta, Li, Zihang, Soled, Heather J., Birnbaum, Michael L., Kumar, Srijan, De Choudhury, Munmun
The rapid evolution of Large Language Models (LLMs) offers promising potential to alleviate the global scarcity of mental health professionals. However, LLMs' alignment with essential mental health counseling competencies remains understudied. We int
Externí odkaz:
http://arxiv.org/abs/2410.22446
An important open question for the current generation of highly controllable quantum devices is understanding which phases can be realized as stable steady-states under local quantum dynamics. In this work, we show how robust steady-state phases with
Externí odkaz:
http://arxiv.org/abs/2410.21402
Publikováno v:
Advances in Neural Networks - ISNN 2019 Proceedings, Part I 16. Lecture Notes in Computer Science(), vol 11554
Among the many variants of RL, an important class of problems is where the state and action spaces are continuous -- autonomous robots, autonomous vehicles, optimal control are all examples of such problems that can lend themselves naturally to reinf
Externí odkaz:
http://arxiv.org/abs/2410.11250