874 citations · 997 across the 8 of their papers we have counts for
9 papers
Brain-inspired feature exaggeration in generative replay for continual learning
Jack Millichamp, Xi Chen
The catastrophic forgetting of previously learnt classes is one of the main obstacles to the successful development of a reliable and accurate generative continual learning model.…
Variable Skipping for Autoregressive Range Density Estimation
Eric Liang, Zongheng Yang, Ion Stoica +3
Deep autoregressive models compute point likelihood estimates of individual data points. However, many applications (i.e., database cardinality estimation) require estimating range…
NeuroCard: One Cardinality Estimator for All Tables
Zongheng Yang, Amog Kamsetty, Sifei Luan +4
Query optimizers rely on accurate cardinality estimates to produce good execution plans. Despite decades of research, existing cardinality estimators are inaccurate for complex que…
Evaluating Protein Transfer Learning with TAPE
Roshan Rao, Nicholas Bhattacharya, Neil Thomas +5
Protein modeling is an increasingly popular area of machine learning research. Semi-supervised learning has emerged as an important paradigm in protein modeling due to the high cos…
Sequence Modeling of Temporal Credit Assignment for Episodic Reinforcement Learning
Yang Liu, Yunan Luo, Yuanyi Zhong +3
Recent advances in deep reinforcement learning algorithms have shown great potential and success for solving many challenging real-world problems, including Go game and robotic app…
Deep Learning by Doing: The NVIDIA Deep Learning Institute and University Ambassador Program
Xi Chen, Gregory S. Gutmann, Joe Bungo
Over the past two decades, High-Performance Computing (HPC) communities have developed many models for delivering education aiming to help students understand and harness the power…