3 citations · 7 across the 4 of their papers we have counts for
4 papers
Maximum n-times Coverage for Vaccine Design
Ge Liu, Alexander Dimitrakakis, Brandon Carter +1
We introduce the maximum -times coverage problem that selects overlays to maximize the summed coverage of weighted elements, where each element must be covered at least …
Information Condensing Active Learning
Siddhartha Jain, Ge Liu, David Gifford
We introduce Information Condensing Active Learning (ICAL), a batch mode model agnostic Active Learning (AL) method targeted at Deep Bayesian Active Learning that focuses on acquir…
Data Efficient Training for Reinforcement Learning with Adaptive Behavior Policy Sharing
Ge Liu, Rui Wu, Heng-Tze Cheng +7
Deep Reinforcement Learning (RL) is proven powerful for decision making in simulated environments. However, training deep RL model is challenging in real world applications such as…
Maximizing Overall Diversity for Improved Uncertainty Estimates in Deep Ensembles
Siddhartha Jain, Ge Liu, Jonas Mueller +1
The inaccuracy of neural network models on inputs that do not stem from the training data distribution is both problematic and at times unrecognized. Model uncertainty estimation c…