no code implementations • 8 Jun 2024 • Hengguan Huang, Xing Shen, Songtao Wang, Dianbo Liu, Hao Wang
Faced with complex problems, the human brain demonstrates a remarkable capacity to transcend sensory input and form latent understandings of perceived world patterns.
1 code implementation • 8 Feb 2024 • Hengguan Huang, Songtao Wang, Hongfu Liu, Hao Wang, Ye Wang
Traditional applications of natural language processing (NLP) in healthcare have predominantly focused on patient-centered services, enhancing patient interactions and care delivery, such as through medical dialogue systems.
1 code implementation • 3 Feb 2024 • Guang-Yuan Hao, Hengguan Huang, Haotian Wang, Jie Gao, Hao Wang
In this paper, we propose the first general method, dubbed composite active learning (CAL), for multi-domain AL. Our approach explicitly considers the domain-level and instance-level information in the problem; CAL first assigns domain-level budgets according to domain-level importance, which is estimated by optimizing an upper error bound that we develop; with the domain-level budgets, CAL then leverages a certain instance-level query strategy to select samples to label from each domain.
no code implementations • 24 Oct 2023 • Xing Shen, Hengguan Huang, Brennan Nichyporuk, Tal Arbel
While deep learning models have achieved remarkable success across a range of medical image analysis tasks, deployment of these models in real clinical contexts requires that they be robust to variability in the acquired images.
no code implementations • 14 Oct 2023 • Hongfu Liu, Hengguan Huang, Ye Wang
However, while acoustic models face similar challenges due to distribution shifts in test-time speech, TTA techniques specifically designed for acoustic modeling in the context of open-world data shifts remain scarce.
no code implementations • 29 Sep 2021 • Xueyang Wu, Hengguan Huang, Hao Wang, Ye Wang, Qian Xu
However, it is challenging for GANs to model distributions of separate non-i. i. d.
1 code implementation • 17 Jul 2021 • Hengguan Huang, Hongfu Liu, Hao Wang, Chang Xiao, Ye Wang
In this paper, we present a probabilistic ordinary differential equation (ODE), called STochastic boundaRy ODE (STRODE), that learns both the timings and the dynamics of time series data without requiring any timing annotations during training.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +4
no code implementations • ICML 2020 • Hengguan Huang, Fuzhao Xue, Hao Wang, Ye Wang
Lying at the core of human intelligence, relational thinking is characterized by initially relying on innumerable unconscious percepts pertaining to relations between new sensory signals and prior knowledge, consequently becoming a recognizable concept or object through coupling and transformation of these percepts.
Automatic Speech Recognition Automatic Speech Recognition (ASR) +1