26 citations · 111 across the 20 of their papers we have counts for
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cs.LG2023
TC-VAE: Uncovering Out-of-Distribution Data Generative Factors
Cristian Meo, Anirudh Goyal, Justin Dauwels
Uncovering data generative factors is the ultimate goal of disentanglement learning. Although many works proposed disentangling generative models able to uncover the underlying gen…
cs.LG2022★ 6 cited
Learning to Solve Multiple-TSP with Time Window and Rejections via Deep Reinforcement Learning
Rongkai Zhang, Cong Zhang, Zhiguang Cao +5
We propose a manager-worker framework based on deep reinforcement learning to tackle a hard yet nontrivial variant of Travelling Salesman Problem (TSP), \ie~multiple-vehicle TSP wi…
cs.LG2019★ 16 cited
Factored Latent-Dynamic Conditional Random Fields for Single and Multi-label Sequence Modeling
Satyajit Neogi, Justin Dauwels
Conditional Random Fields (CRF) are frequently applied for labeling and segmenting sequence data. Morency et al. (2007) introduced hidden state variables in a labeled CRF structure…