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20192026
most citedPredicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network

82 citations · 198 across the 13 of their papers we have counts for

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5 papers · 1 filter

cs.LG2026

Neural Wasserstein Splines: Representation-Invariant Second-Order Priors for Trajectory Inference

Amartya Banerjee, Harlin Lee, Caroline Moosmüller

Population dynamics are often observed only as unpaired snapshots, which leave the evolution between measurements underdetermined. Second-order regularization can constrain it, but…

cs.LG2026

Uncovering Trajectory and Topological Signatures in Multimodal Pediatric Sleep Embeddings

Scott Ye, Harlin Lee

While generative models have shown promise in pediatric sleep analysis, the latent structure of their multimodal embeddings remains poorly understood. This work investigates sessio…

cs.LG2026

Fused Gromov-Wasserstein Distance with Feature Selection

Harlin Lee, Ying Yu, Mingxin Li +1

Fused Gromov-Wasserstein (FGW) distances provide a principled framework for comparing objects by jointly aligning structure and node features. However, existing FGW formulations tr…

cs.LG2024★ 2 cited

PedSleepMAE: Generative Model for Multimodal Pediatric Sleep Signals

Saurav R. Pandey, Aaqib Saeed, Harlin Lee

Pediatric sleep is an important but often overlooked area in health informatics. We present PedSleepMAE, a generative model that fully leverages multimodal pediatric sleep signals…

cs.LG2024

Efficient Trajectory Inference in Wasserstein Space Using Consecutive Averaging

Amartya Banerjee, Harlin Lee, Nir Sharon +1

Capturing data from dynamic processes through cross-sectional measurements is seen in many fields, such as computational biology. Trajectory inference deals with the challenge of r…