517 citations · 789 across the 25 of their papers we have counts for
6 papers · 1 filter
Scalable Set Encoding with Universal Mini-Batch Consistency and Unbiased Full Set Gradient Approximation
Jeffrey Willette, Seanie Lee, Bruno Andreis +3
Recent work on mini-batch consistency (MBC) for set functions has brought attention to the need for sequentially processing and aggregating chunks of a partitioned set while guaran…
StyleTalker: One-shot Style-based Audio-driven Talking Head Video Generation
Dongchan Min, Minyoung Song, Eunji Ko +1
We propose StyleTalker, a novel audio-driven talking head generation model that can synthesize a video of a talking person from a single reference image with accurately audio-synce…
BiTAT: Neural Network Binarization with Task-dependent Aggregated Transformation
Geon Park, Jaehong Yoon, Haiyang Zhang +3
Neural network quantization aims to transform high-precision weights and activations of a given neural network into low-precision weights/activations for reduced memory usage and c…
Exploring Chemical Space with Score-based Out-of-distribution Generation
Seul Lee, Jaehyeong Jo, Sung Ju Hwang
A well-known limitation of existing molecular generative models is that the generated molecules highly resemble those in the training set. To generate truly novel molecules that ma…
Set-based Meta-Interpolation for Few-Task Meta-Learning
Seanie Lee, Bruno Andreis, Kenji Kawaguchi +2
Meta-learning approaches enable machine learning systems to adapt to new tasks given few examples by leveraging knowledge from related tasks. However, a large number of meta-traini…
Skill-based Meta-Reinforcement Learning
Taewook Nam, Shao-Hua Sun, Karl Pertsch +2
While deep reinforcement learning methods have shown impressive results in robot learning, their sample inefficiency makes the learning of complex, long-horizon behaviors with real…