no code implementations • 21 Nov 2022 • Nhat M. Nguyen, Hieu T. Tran, Minh V. Duong, Hanh Bui, Kenneth Tran
We present a differentiable greenhouse simulation model based on physical processes whose parameters can be obtained by training from real data.
no code implementations • 25 Sep 2019 • Tung-Long Vuong, Han Nguyen, Hai Pham, Kenneth Tran
Under this framework, the objective function can represented end-to-end as a single computational graph, which allows seamless policy gradient computation via backpropagation through the models.
no code implementations • 25 Jun 2019 • Tung-Long Vuong, Kenneth Tran
Model-based reinforcement learning has the potential to be more sample efficient than model-free approaches.
2 code implementations • NeurIPS 2019 • Aditya Grover, Jiaming Song, Alekh Agarwal, Kenneth Tran, Ashish Kapoor, Eric Horvitz, Stefano Ermon
A standard technique to correct this bias is importance sampling, where samples from the model are weighted by the likelihood ratio under model and true distributions.
no code implementations • ICLR Workshop DeepGenStruct 2019 • Aditya Grover, Jiaming Song, Ashish Kapoor, Kenneth Tran, Alekh Agarwal, Eric Horvitz, Stefano Ermon
A standard technique to correct this bias is by importance weighting samples from the model by the likelihood ratio under the model and true distributions.
1 code implementation • 12 Jun 2018 • Michael Pan, Peter J. Gawthrop, Kenneth Tran, Joseph Cursons, Edmund J. Crampin
Membrane transporters contribute to the regulation of the internal environment of cells by translocating substrates across cell membranes.
Biomolecules
1 code implementation • CVPR 2017 • Zhe Gan, Chuang Gan, Xiaodong He, Yunchen Pu, Kenneth Tran, Jianfeng Gao, Lawrence Carin, Li Deng
The degree to which each member of the ensemble is used to generate an image caption is tied to the image-dependent probability of the corresponding tag.
no code implementations • 30 Mar 2016 • Kenneth Tran, Xiaodong He, Lei Zhang, Jian Sun, Cornelia Carapcea, Chris Thrasher, Chris Buehler, Chris Sienkiewicz
We present an image caption system that addresses new challenges of automatically describing images in the wild.