activity
20232025
most citedFrom Aleatoric to Epistemic: Exploring Uncertainty Quantification Techniques in Artificial Intelligence

9 citations · 20 across the 6 of their papers we have counts for

collaborators

6 papers

q-bio.NC2025★ 1 cited

MIMIC-MJX: Neuromechanical Emulation of Animal Behavior

Charles Y. Zhang, Yuanjia Yang, Aidan Sirbu +25

The primary output of the nervous system is movement and behavior. While recent advances have democratized pose tracking during complex behavior, kinematic trajectories alone provi…

q-bio.GN2025★ 2 cited

From In Silico to In Vitro: A Comprehensive Guide to Validating Bioinformatics Findings

Tianyang Wang, Silin Chen, Yunze Wang +18

Translating computational predictions into experimentally validated biological knowledge remains one of the central challenges in modern bioinformatics. This review critically exam…

cs.AI2025★ 9 cited

From Aleatoric to Epistemic: Exploring Uncertainty Quantification Techniques in Artificial Intelligence

Tianyang Wang, Yunze Wang, Jun Zhou +16

Uncertainty quantification (UQ) is a critical aspect of artificial intelligence (AI) systems, particularly in high-risk domains such as healthcare, autonomous systems, and financia…

cs.CV2024★ 1 cited

From Pixels to Prose: Advancing Multi-Modal Language Models for Remote Sensing

Xintian Sun, Benji Peng, Charles Zhang +10

Remote sensing has evolved from simple image acquisition to complex systems capable of integrating and processing visual and textual data. This review examines the development and…

cs.CL2024★ 6 cited

From Word Vectors to Multimodal Embeddings: Techniques, Applications, and Future Directions For Large Language Models

Charles Zhang, Benji Peng, Xintian Sun +14

Word embeddings and language models have transformed natural language processing (NLP) by facilitating the representation of linguistic elements in continuous vector spaces. This r…

cs.CV2023★ 1 cited

AptSim2Real: Approximately-Paired Sim-to-Real Image Translation

Charles Y Zhang, Ashish Shrivastava

Advancements in graphics technology has increased the use of simulated data for training machine learning models. However, the simulated data often differs from real-world data, cr…