影响力指数
论文质量、代表作、近期表现、广度与样本量置信度综合计算
14.47/100
超过 44.2%
全站排名 #35,911
发表论文16 篇
平均评分
年均产出5.3 篇/年
Sandeep Kumar
研究方向
Graphical Models · Geometric Deep Learning · Large Scale Optimization · Sampling · Heavy-Tailed Time Series · Missing Data · Non-Convex Optimization · Decentralized Optimization
25
GraphFLEx: Structure Learning $\underline{\text{F}}$ramework for $\underline{\text{L}}$arge $\underline{\text{Ex}}$panding $\underline{\text{Graph}}$s
ICLR 2026Rejected
三作22
AH-UGC: $\underline{\text{A}}$daptive and $\underline{\text{H}}$eterogeneous-$\underline{\text{U}}$niversal $\underline{\text{G}}$raph $\underline{\text{C}}$oarsening
ICLR 2026Rejected
三作45
Graph-to-Sequence Generation Beyond Autoregressive Models: A Graph-Aware Diffusion Framework
ICLR 2026Desk Rejected
通讯20
SENSE: $\underline{\text{SEN}}$sing Similarity $\underline{\text{SE}}$eing Structure
ICLR 2026Rejected
三作36
AH-UGC: $\underline{\text{A}}$daptive and $\underline{\text{H}}$eterogeneous-$\underline{\text{U}}$niversal $\underline{\text{G}}$raph $\underline{\text{C}}$oarsening
NeurIPS 2025Rejected
三作30
SENSE: $\underline{\text{SEN}}$sing Similarity $\underline{\text{SE}}$eing Structure
NeurIPS 2025Rejected
三作23
GraphFLEx: Structure Learning $\underline{\text{F}}$ramework for $\underline{\text{L}}$arge $\underline{\text{Ex}}$panding $\underline{\text{Graph}}$s
NeurIPS 2025Rejected
三作7
GraphFLEx: Structure Learning $\underline{\text{F}}$ramework for $\underline{\text{L}}$arge $\underline{\text{Ex}}$panding $\underline{\text{Graph}}$s
ICML 2025Rejected
三作22
Feature Driven Graph Coarsening for Scaling Graph Representation Learning
ICLR 2025Rejected
通讯6
Task and Model Agnostic Differentially Private Graph Neural Networks via Coarsening
ICLR 2025Rejected
三作6
Coarsening to Conceal: Enabling Privacy-Preserving Federated Learning for Graph Data
ICLR 2025Rejected
通讯