Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Sun, Kunyang"'
Autor:
Li, Jie, Guan, Xingyi, Zhang, Oufan, Sun, Kunyang, Wang, Yingze, Bagni, Dorian, Head-Gordon, Teresa
Many physics-based and machine-learned scoring functions (SFs) used to predict protein-ligand binding free energies have been trained on the PDBBind dataset. However, it is controversial as to whether new SFs are actually improving since the general,
Externí odkaz:
http://arxiv.org/abs/2308.09639
Unsupervised domain adaptive object detection is a challenging vision task where object detectors are adapted from a label-rich source domain to an unlabeled target domain. Recent advances prove the efficacy of the adversarial based domain alignment
Externí odkaz:
http://arxiv.org/abs/2303.15377
Autor:
Du, Matthew, Pérez-Sánchez, Juan B., Campos-Gonzalez-Angulo, Jorge A., Koner, Arghadip, Mellini, Federico, Pannir-Sivajothi, Sindhana, Poh, Yong Rui, Schwennicke, Kai, Sun, Kunyang, Wildenberg, Stephan van den, Karzen, Dylan, Barron, Alec, Yuen-Zhou, Joel
Topological insulators are insulators in the bulk but feature chiral energy propagation along the boundary. This property is topological in nature and therefore robust to disorder. Originally discovered in electronic materials, topologically protecte
Externí odkaz:
http://arxiv.org/abs/2301.08356
Autor:
Mirza, M. Jehanzeb, Shin, Inkyu, Lin, Wei, Schriebl, Andreas, Sun, Kunyang, Choe, Jaesung, Possegger, Horst, Kozinski, Mateusz, Kweon, In So, Yoon, Kun-Jin, Bischof, Horst
Our MATE is the first Test-Time-Training (TTT) method designed for 3D data, which makes deep networks trained for point cloud classification robust to distribution shifts occurring in test data. Like existing TTT methods from the 2D image domain, MAT
Externí odkaz:
http://arxiv.org/abs/2211.11432
Generation of drug-like molecules with high binding affinity to target proteins remains a difficult and resource-intensive task in drug discovery. Existing approaches primarily employ reinforcement learning, Markov sampling, or deep generative models
Externí odkaz:
http://arxiv.org/abs/2206.09010
Although action recognition has achieved impressive results over recent years, both collection and annotation of video training data are still time-consuming and cost intensive. Therefore, image-to-video adaptation has been proposed to exploit labeli
Externí odkaz:
http://arxiv.org/abs/2203.16244
Autor:
Li, Jie, Zhang, Oufan, Wang, Yingze, Sun, Kunyang, Guan, Xingyi, Bagni, Dorian, Haghighatlari, Mojtaba, Kearns, Fiona L., Parks, Conor, Amaro, Rommie E., Head-Gordon, Teresa
The viability of a new drug molecule is a time and resource intensive task that makes computer-aided assessments a vital approach to rapid drug discovery. Here we develop a machine learning algorithm, iMiner, that generates novel inhibitor molecules
Externí odkaz:
http://arxiv.org/abs/2110.01806
Instance segmentation is one of the fundamental vision tasks. Recently, fully convolutional instance segmentation methods have drawn much attention as they are often simpler and more efficient than two-stage approaches like Mask R-CNN. To date, almos
Externí odkaz:
http://arxiv.org/abs/2001.00309
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.