← Authors

Abir De

37 papers · 2016–2025 · 8 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (10) 🌍 Conference Polyglot (8) 🌈 Renaissance Researcher (7) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (17) πŸƒ Academic Marathon (9) 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (3) 🀝 Dynamic Duo (12) πŸ† Keyword Champion (2) πŸ† Grand Slam πŸ’Ž Century Club (37) πŸ”₯ Unstoppable (10) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (163) ⚑ Prolific Year (6)

Conferences

NIPS (13) AAAI (10) ICML (6) AISTATS (2) ICLR (2) JMLR (2) IJCAI (1) UAI (1)

Top co-authors

Soumen Chakrabarti (12) Indradyumna Roy (8) Niloy Ganguly (6) Manuel Gomez Rodriguez (5) Rishabh Iyer (4) Eeshaan Jain (4) Sourangshu Bhattacharya (3) Durga S (3) Ganesh Ramakrishnan (3) Bidisha Samanta (3)

Research topics

Differential Privacy (1) Probability (1)

Keywords

temporal point process (7) neural network (6) graph neural network (5) submodular optimization (4) event sequence (3) graph retrieval (3) data subset selection (3) variational autoencoder (3) generative model (3) marked temporal point process (3) variational inference (2) molecular graph (2) combinatorial optimization (2) subgraph matching (2) latent representation (2) greedy algorithm (2) node embedding (2) locality sensitive hashing (2) causal inference (2) markov decision process (2)

Papers

Differentiable Adversarial Attacks for Marked Temporal Point Processes AAAI 2025
Clique Number Estimation via Differentiable Functions of Adjacency Matrix Permutations ICLR 2025
Charting the Design Space of Neural Graph Representations for Subgraph Matching ICLR 2025
Position: Graph Matching Systems Deserve Better Benchmarks ICML 2025
Learning Condensed Graph via Differentiable Atom Mapping for Reaction Yield Prediction ICML 2025
Iteratively Refined Early Interaction Alignment for Subgraph Matching based Graph Retrieval NIPS 2024
Continuous Treatment Effect Estimation Using Gradient Interpolation and Kernel Smoothing AAAI 2024
Generator Assisted Mixture of Experts for Feature Acquisition in Batch AAAI 2024
Graph Edit Distance with General Costs Using Neural Set Divergence NIPS 2024
Efficient Data Subset Selection to Generalize Training Across Models: Transductive and Inductive Networks NIPS 2023
Locality Sensitive Hashing in Fourier Frequency Domain For Soft Set Containment Search NIPS 2023
Differentiable Change-point Detection With Temporal Point Processes AISTATS 2023
Discrete Continuous Optimization Framework for Simultaneous Clustering and Training in Mixture Models ICML 2023
VarScene: A Deep Generative Model for Realistic Scene Graph Synthesis ICML 2022
Neural Estimation of Submodular Functions with Applications to Differentiable Subset Selection NIPS 2022
Learning Recourse on Instance Environment to Enhance Prediction Accuracy NIPS 2022
Maximum Common Subgraph Guided Graph Retrieval: Late and Early Interaction Networks NIPS 2022
Learning Temporal Point Processes for Efficient Retrieval of Continuous Time Event Sequences AAAI 2022
Interpretable Neural Subgraph Matching for Graph Retrieval AAAI 2022
Training Data Subset Selection for Regression with Controlled Generalization Error ICML 2021
Classification Under Human Assistance AAAI 2021
Differentially Private Link Prediction with Protected Connections AAAI 2021
Counterfactual Explanations in Sequential Decision Making Under Uncertainty NIPS 2021
Learning Temporal Point Processes with Intermittent Observations AISTATS 2021
Training for the Future: A Simple Gradient Interpolation Loss to Generalize Along Time NIPS 2021
Differentiable Learning Under Triage NIPS 2021
Learning to Select Exogenous Events for Marked Temporal Point Process NIPS 2021
Adversarial Permutation Guided Node Representations for Link Prediction AAAI 2021
GRAD-MATCH: Gradient Matching based Data Subset Selection for Efficient Deep Model Training ICML 2021
On the design of consequential ranking algorithms UAI 2020
Regression under Human Assistance AAAI 2020
NEVAE: A Deep Generative Model for Molecular Graphs JMLR 2020
NeVAE: A Deep Generative Model for Molecular Graphs AAAI 2019
Deep Reinforcement Learning of Marked Temporal Point Processes NIPS 2018
Steering Social Activity: A Stochastic Optimal Control Point Of View JMLR 2018
LMPP: A Large Margin Point Process Combining Reinforcement and Competition for Modeling Hashtag Popularity IJCAI 2017
Learning and Forecasting Opinion Dynamics in Social Networks NIPS 2016