most citedScaling physics-informed hard constraints with mixture-of-experts

3 citations · 5 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Delayed Bidirectional Alignment via Disentangled Audio Semantics for Audio-Visual Segmentation

Jingqi Tian, Yiheng Du, Haoji Zhang +6

Audio-Visual Segmentation (AVS) aims to localize sound-producing objects at the pixel level by integrating auditory and visual cues. However, existing methods often struggle with m…

cs.LG2025

EddyFormer: Accelerated Neural Simulations of Three-Dimensional Turbulence at Scale

Yiheng Du, Aditi S. Krishnapriyan

Computationally resolving turbulence remains a central challenge in fluid dynamics due to its multi-scale interactions. Fully resolving large-scale turbulence through direct numeri…

cs.CV2025

AlignedGen: Aligning Style Across Generated Images

Jiexuan Zhang, Yiheng Du, Qian Wang +3

Despite their generative power, diffusion models struggle to maintain style consistency across images conditioned on the same style prompt, hindering their practical deployment in…

cs.LG2024★ 3 cited

Scaling physics-informed hard constraints with mixture-of-experts

Nithin Chalapathi, Yiheng Du, Aditi Krishnapriyan

Imposing known physical constraints, such as conservation laws, during neural network training introduces an inductive bias that can improve accuracy, reliability, convergence, and…

cs.LG2024★ 2 cited

Neural Spectral Methods: Self-supervised learning in the spectral domain

Yiheng Du, Nithin Chalapathi, Aditi Krishnapriyan

We present Neural Spectral Methods, a technique to solve parametric Partial Differential Equations (PDEs), grounded in classical spectral methods. Our method uses orthogonal bases…