Zobrazeno 1 - 10
of 428
pro vyhledávání: '"Dhawal, P."'
Fluid flows are intrinsically characterized via the topology and dynamics of underlying vortex lines. Turbulence in common fluids like water and air, mathematically described by the incompressible Navier-Stokes equations (INSE), engenders spontaneous
Externí odkaz:
http://arxiv.org/abs/2409.13125
Training a model-free reinforcement learning agent requires allowing the agent to sufficiently explore the environment to search for an optimal policy. In safety-constrained environments, utilizing unsupervised exploration or a non-optimal policy may
Externí odkaz:
http://arxiv.org/abs/2408.00997
We present ICU-Sepsis, an environment that can be used in benchmarks for evaluating reinforcement learning (RL) algorithms. Sepsis management is a complex task that has been an important topic in applied RL research in recent years. Therefore, MDPs t
Externí odkaz:
http://arxiv.org/abs/2406.05646
Software security continues to be a critical concern for programs implemented in low-level programming languages such as C and C++. Many defenses have been proposed in the current literature, each with different trade-offs including performance, comp
Externí odkaz:
http://arxiv.org/abs/2405.12513
Traditional Radiance Field (RF) representations capture details of a specific scene and must be trained afresh on each scene. Semantic feature fields have been added to RFs to facilitate several segmentation tasks. Generalised RF representations lear
Externí odkaz:
http://arxiv.org/abs/2402.04632
Autor:
Naik, Shanthika, Singh, Kunwar, Srivastava, Astitva, Sirikonda, Dhawal, Raj, Amit, Jampani, Varun, Sharma, Avinash
We propose a novel self-supervised framework for retargeting non-parameterized 3D garments onto 3D human avatars of arbitrary shapes and poses, enabling 3D virtual try-on (VTON). Existing self-supervised 3D retargeting methods only support parametric
Externí odkaz:
http://arxiv.org/abs/2401.03108
Autor:
Gupta, Dhawal, Jordan, Scott M., Chaudhari, Shreyas, Liu, Bo, Thomas, Philip S., da Silva, Bruno Castro
In this paper, we introduce a fresh perspective on the challenges of credit assignment and policy evaluation. First, we delve into the nuances of eligibility traces and explore instances where their updates may result in unexpected credit assignment
Externí odkaz:
http://arxiv.org/abs/2312.12972
Designing reward functions for efficiently guiding reinforcement learning (RL) agents toward specific behaviors is a complex task. This is challenging since it requires the identification of reward structures that are not sparse and that avoid inadve
Externí odkaz:
http://arxiv.org/abs/2310.19007
During the last stage of RLHF, a large language model is aligned to human intents via PPO training, a process that generally requires large-scale computational resources. In this technical report, we empirically investigate an efficient implementatio
Externí odkaz:
http://arxiv.org/abs/2309.09055
Autor:
Buaria, Dhawal, Pumir, Alain
We investigate the role of pressure, via its Hessian tensor $\mathbf{H}$, on amplification of vorticity and strain-rate and contrast it with other inviscid nonlinear mechanisms. Results are obtained from direct numerical simulations of isotropic turb
Externí odkaz:
http://arxiv.org/abs/2308.03902