no code implementations • 29 Jan 2024 • Yuhan Chen, Lumei Su, Lihua Chen, Zhiwei Lin
Experimental implementations were conducted under constrained computational and memory resources, evaluating the proposed method's performance on benchmark datasets including GQA, CLEVR, and VizWiz-VQA-Grounding.
no code implementations • 9 Aug 2022 • Lihua Chen, Ning Yang, Philip S Yu
First, the existing methods often lack the simultaneous consideration of the global stability and local fluctuation of user preference, which might degrade the learning of a user's current preference.
no code implementations • 4 Nov 2020 • Rohit Batra, Hanjun Dai, Tran Doan Huan, Lihua Chen, Chiho Kim, Will R. Gutekunst, Le Song, Rampi Ramprasad
The design/discovery of new materials is highly non-trivial owing to the near-infinite possibilities of material candidates, and multiple required property/performance objectives.
no code implementations • 1 Nov 2020 • Lihua Chen, Ghanshyam Pilania, Rohit Batra, Tran Doan Huan, Chiho Kim, Christopher Kuenneth, Rampi Ramprasad
Artificial intelligence (AI) based approaches are beginning to impact several domains of human life, science and technology.
no code implementations • 28 Oct 2020 • Christopher Künneth, Arunkumar Chitteth Rajan, Huan Tran, Lihua Chen, Chiho Kim, Rampi Ramprasad
Compared to conventional single-task learning models (that are trained on individual property datasets independently), the multi-task approach is accurate, efficient, scalable, and amenable to transfer learning as more data on the same or different properties become available.
no code implementations • 8 Dec 2018 • Fang Liu, Lihua Chen, Richard Kijowski, Li Feng
The undersampled images are generated by a fixed undersampling pattern in the training, and the trained network is then applied to reconstruct new images acquired with the same pattern in the inference.