← Authors

Mark Coates

27 papers · 2019–2025 · 6 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (6) 🌈 Renaissance Researcher (6) 🌍 Conference Polyglot (6) 🐝 Cross-Pollinator (12) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (13) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🀝 Dynamic Duo (15) πŸ‘‘ Triple Crown πŸ† Grand Slam πŸ”¬ Deep Specialist (10) πŸ† Keyword Champion (2) πŸš€ Conference Pioneer ⚑ Prolific Year (7) πŸ—ƒοΈ Keyword Collector (121) πŸ’Ž Century Club (27) πŸ”₯ Unstoppable (7)

Conferences

AAAI (8) ICML (8) AISTATS (6) NIPS (3) ICLR (1) UAI (1)

Top co-authors

Yingxue Zhang (15) Florence Regol (9) Liheng Ma (8) Soumyasundar Pal (8) Antonios Valkanas (4) Xue Liu (3) Chen Ma (3) Jianye Hao (3) Yitian Zhang (3) Boris N. Oreshkin (3)

Keywords

graph neural network (10) node classification (3) bayesian inference (3) neural tangent kernel (2) posterior inference (2) variational inference (2) spatio-temporal forecasting (2) semi-supervised learning (2) generative model (2) bayesian graph neural network (2) categorical datum (2) collaborative filtering (1) link prediction (1) boolean satisfiability (1) graph learning (1) catastrophic forgetting (1) transformer architecture (1) bayesian learning (1) data augmentation (1) contrastive learning (1)

Papers

When to retrain a machine learning model ICML 2025
MODL: Multilearner Online Deep Learning AISTATS 2025
SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting ICML 2025
InnerThoughts: Disentangling Representations and Predictions in Large Language Models AISTATS 2025
Jointly-Learned Exit and Inference for a Dynamic Neural Network ICLR 2024
HardCore Generation: Generating Hard UNSAT Problems for Data Augmentation NIPS 2024
Interacting Diffusion Processes for Event Sequence Forecasting ICML 2024
CKGConv: General Graph Convolution with Continuous Kernels ICML 2024
Categorical Generative Model Evaluation via Synthetic Distribution Coarsening AISTATS 2024
Multi-resolution Time-Series Transformer for Long-term Forecasting AISTATS 2024
Neighbor Auto-Grouping Graph Neural Networks for Handover Parameter Configuration in Cellular Network AAAI 2023
Graph Inductive Biases in Transformers without Message Passing ICML 2023
Spectral Augmentations for Graph Contrastive Learning AISTATS 2023
Neural Graph Generation from Graph Statistics NIPS 2023
Bidirectional Learning for Offline Model-based Biological Sequence Design ICML 2023
Structure Aware Incremental Learning with Personalized Imitation Weights for Recommender Systems AAAI 2023
Diffusing Gaussian Mixtures for Generating Categorical Data AAAI 2023
Bidirectional Learning for Offline Infinite-width Model-based Optimization NIPS 2022
Bag Graph: Multiple Instance Learning Using Bayesian Graph Neural Networks AAAI 2022
RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting ICML 2021
Detection and Defense of Topological Adversarial Attacks on Graphs AISTATS 2021
FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting AAAI 2021
Knowledge-Enhanced Top-K Recommendation in PoincarΓ© Ball AAAI 2021
Non Parametric Graph Learning for Bayesian Graph Neural Networks UAI 2020
Active Learning on Attributed Graphs via Graph Cognizant Logistic Regression and Preemptive Query Generation ICML 2020
Memory Augmented Graph Neural Networks for Sequential Recommendation AAAI 2020
Bayesian Graph Convolutional Neural Networks for Semi-Supervised Classification AAAI 2019