Zobrazeno 1 - 10
of 424
pro vyhledávání: '"Ji, Shuiwang"'
Autor:
Li, Xiner, Wang, Limei, Luo, Youzhi, Edwards, Carl, Gui, Shurui, Lin, Yuchao, Ji, Heng, Ji, Shuiwang
We consider molecule generation in 3D space using language models (LMs), which requires discrete tokenization of 3D molecular geometries. Although tokenization of molecular graphs exists, that for 3D geometries is largely unexplored. Here, we attempt
Externí odkaz:
http://arxiv.org/abs/2408.10120
Structure-based drug design (SBDD) is crucial for developing specific and effective therapeutics against protein targets but remains challenging due to complex protein-ligand interactions and vast chemical space. Although language models (LMs) have e
Externí odkaz:
http://arxiv.org/abs/2408.09730
Autor:
Wang, Ziqi, Zhang, Hanlin, Li, Xiner, Huang, Kuan-Hao, Han, Chi, Ji, Shuiwang, Kakade, Sham M., Peng, Hao, Ji, Heng
Position bias has proven to be a prevalent issue of modern language models (LMs), where the models prioritize content based on its position within the given context. This bias often leads to unexpected model failures and hurts performance, robustness
Externí odkaz:
http://arxiv.org/abs/2407.01100
In many scientific fields, large language models (LLMs) have revolutionized the way text and other modalities of data (e.g., molecules and proteins) are handled, achieving superior performance in various applications and augmenting the scientific dis
Externí odkaz:
http://arxiv.org/abs/2406.10833
We consider achieving equivariance in machine learning systems via frame averaging. Current frame averaging methods involve a costly sum over large frames or rely on sampling-based approaches that only yield approximate equivariance. Here, we propose
Externí odkaz:
http://arxiv.org/abs/2406.07598
We consider the prediction of general tensor properties of crystalline materials, including dielectric, piezoelectric, and elastic tensors. A key challenge here is how to make the predictions satisfy the unique tensor equivariance to O(3) group and i
Externí odkaz:
http://arxiv.org/abs/2406.12888
Test-time adaptation (TTA) addresses distribution shifts for streaming test data in unsupervised settings. Currently, most TTA methods can only deal with minor shifts and rely heavily on heuristic and empirical studies. To advance TTA under domain sh
Externí odkaz:
http://arxiv.org/abs/2404.05094
Autor:
Zhang, Xuan, Helwig, Jacob, Lin, Yuchao, Xie, Yaochen, Fu, Cong, Wojtowytsch, Stephan, Ji, Shuiwang
We consider using deep neural networks to solve time-dependent partial differential equations (PDEs), where multi-scale processing is crucial for modeling complex, time-evolving dynamics. While the U-Net architecture with skip connections is commonly
Externí odkaz:
http://arxiv.org/abs/2403.19507
Crystal structures are characterized by atomic bases within a primitive unit cell that repeats along a regular lattice throughout 3D space. The periodic and infinite nature of crystals poses unique challenges for geometric graph representation learni
Externí odkaz:
http://arxiv.org/abs/2403.11857
Neural algorithmic reasoning is an emerging research direction that endows neural networks with the ability to mimic algorithmic executions step-by-step. A common paradigm in existing designs involves the use of historical embeddings in predicting th
Externí odkaz:
http://arxiv.org/abs/2403.04929