Summary of Jinns: a Jax Library For Physics-informed Neural Networks, by Hugo Gangloff et al.
jinns: a JAX Library for Physics-Informed Neural Networksby Hugo Gangloff, Nicolas JouvinFirst submitted to arxiv…
jinns: a JAX Library for Physics-Informed Neural Networksby Hugo Gangloff, Nicolas JouvinFirst submitted to arxiv…
VideoDPO: Omni-Preference Alignment for Video Diffusion Generationby Runtao Liu, Haoyu Wu, Zheng Ziqiang, Chen Wei,…
Preconditioned Subspace Langevin Monte Carloby Tyler Maunu, Jiayi YaoFirst submitted to arxiv on: 18 Dec…
Federated t-SNE and UMAP for Distributed Data Visualizationby Dong Qiao, Xinxian Ma, Jicong FanFirst submitted…
Indirect Query Bayesian Optimization with Integrated Feedbackby Mengyan Zhang, Shahine Bouabid, Cheng Soon Ong, Seth…
Marigold-DC: Zero-Shot Monocular Depth Completion with Guided Diffusionby Massimiliano Viola, Kevin Qu, Nando Metzger, Bingxin…
On the Hardness of Training Deep Neural Networks Discretelyby Ilan Doron-AradFirst submitted to arxiv on:…
BOIDS: High-dimensional Bayesian Optimization via Incumbent-guided Direction Lines and Subspace Embeddingsby Lam Ngo, Huong Ha,…
An Advantage-based Optimization Method for Reinforcement Learning in Large Action Spaceby Hai Lin, Cheng Huang,…
DeepSN: A Sheaf Neural Framework for Influence Maximizationby Asela Hevapathige, Qing Wang, Ahad N. ZehmakanFirst…