Mark Coates
27 papers · 2019–2025 · 6 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (53) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Grand Slam
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Keyword Champion
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Dynamic Duo
(15)
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Triple Crown
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Deep Specialist
(11)
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Conference Pioneer
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Unstoppable Β· Bronze
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Prolific Year Β· Productive
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Century Club Β· Bronze
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Renaissance Researcher
(5)
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Keyword Collector
(158)
Top co-authors
Research topics
Machine Learning
(24)
Deep Learning
(19)
Core Methods
(16)
Architectures
(14)
Learning Types Β· Machine Learning
(12)
Application Areas
(9)
Artificial Intelligence
(8)
Optimization & Theory
(7)
Learning Types Β· Deep Learning
(5)
Data Science & Analytics
(4)
Core AI
(4)
Models
(4)
Applications
(3)
Bayesian & Probabilistic
(3)
Computer Science
(2)
Keywords
graph neural network
(10)
bayesian inference
(3)
node classification
(3)
hidden state
(2)
variational inference
(2)
posterior inference
(2)
spatiotemporal forecasting
(2)
graph transformer
(2)
neural tangent kernel
(2)
categorical data
(2)
incremental learning
(2)
generative model
(2)
bayesian graph neural network
(2)
semi-supervised learning
(2)
logistic regression
(1)
catastrophic forgetting
(1)
bayesian learning
(1)
contrastive learning
(1)
transformer architecture
(1)
black-box optimization
(1)
Papers
InnerThoughts: Disentangling Representations and Predictions in Large Language Models
AISTATS 2025
MODL: Multilearner Online Deep Learning
AISTATS 2025
SKOLR: Structured Koopman Operator Linear RNN for Time-Series Forecasting
ICML 2025
When to retrain a machine learning model
ICML 2025
Categorical Generative Model Evaluation via Synthetic Distribution Coarsening
AISTATS 2024
CKGConv: General Graph Convolution with Continuous Kernels
ICML 2024
HardCore Generation: Generating Hard UNSAT Problems for Data Augmentation
NeurIPS 2024
Interacting Diffusion Processes for Event Sequence Forecasting
ICML 2024
Jointly-Learned Exit and Inference for a Dynamic Neural Network
ICLR 2024
Multi-resolution Time-Series Transformer for Long-term Forecasting
AISTATS 2024
Bidirectional Learning for Offline Model-based Biological Sequence Design
ICML 2023
Diffusing Gaussian Mixtures for Generating Categorical Data
AAAI 2023
Graph Inductive Biases in Transformers without Message Passing
ICML 2023
Neighbor Auto-Grouping Graph Neural Networks for Handover Parameter Configuration in Cellular Network
AAAI 2023
Neural Graph Generation from Graph Statistics
NeurIPS 2023
Spectral Augmentations for Graph Contrastive Learning
AISTATS 2023
Structure Aware Incremental Learning with Personalized Imitation Weights for Recommender Systems
AAAI 2023
Bag Graph: Multiple Instance Learning Using Bayesian Graph Neural Networks
AAAI 2022
Bidirectional Learning for Offline Infinite-width Model-based Optimization
NeurIPS 2022
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
RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting
ICML 2021
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
Non Parametric Graph Learning for Bayesian Graph Neural Networks
UAI 2020
Bayesian Graph Convolutional Neural Networks for Semi-Supervised Classification
AAAI 2019