Amos Storkey
Professor
Leads a group working on machine learning, reinforcement learning and language models, with interests in efficient deep learning and probabilistic methods.
Amos Storkey's lab at Edinburgh works on reinforcement learning, probabilistic & causal inference and efficient training & inference. 61 papers since 2023, 33 at top venues, mostly ICML and ICLR. 18 PhD students.
At a glance
- papers, 2023–2026
- 16/ year
- at T1 venues
- 54%
- PhD students
- 18
- MS students
- 0
- alumni listed
- —
Papers by yearfrom the lab homepage, 2023–2026
- 17 papers2026 · T1 12 · collecting
- 10 papers2025 · T1 3
- 19 papers2024 · T1 11
- 15 papers2023 · T1 7
T1 venuesOtherVenues: ICML, ICLR, NeurIPS, CVPR, AISTATS
Research focuspaper titles that use each topic's words
- Reinforcement learning20 papers
- Efficient training & inference7 papers
- Probabilistic & causal inference6 papers
- probabilistic1 paper
- efficient deep0 papers
Paper list
From the lab homepage.
202617 papers
- UAI (T1)A Sobering Look at Tabular Data Generation with Probabilistic Circuits (opens in a new tab)
- Reinforcement Learning and Video Games Workshop @ RLCBenchmarking Language Agents on Open-Ended Multi-Agent Coordination in Game Worlds (opens in a new tab)
- AutoMLEvolutionary Architecture Search through Grammar-Based Sequence Alignment (opens in a new tab)
- ICML (T1)Kalman Linear Attention: Parallel Bayesian Filtering for Efficient Language Modeling and State Tracking (opens in a new tab)
- ICML (T1)Magnitude Distance: A Geometric Measure of Dataset Similarity (opens in a new tab)
- ICLR (T1)Meta-Adaptive Prompt Distillation for Few Shot Questioning and Answering (opens in a new tab)
- ICML (T1)Model Diffusion for Certifiable Few-shot Transfer Learning (opens in a new tab)
- UAI (T1)Model Merging is Secretly Certifiable: Non-Vacuous Generalisation Bounds for Low-Shot Learning (opens in a new tab)
- ICLR (T1)Object-Centric World Models from Few-Shot Annotations for Sample-Efficient Reinforcement Learning (opens in a new tab)
- AutoMLONNX-Net: Towards Universal Representations and Instant Performance Prediction for Neural Architectures (opens in a new tab)
- ICML (T1)Position: Agents Should Invoke External Tools Only When Epistemically Necessary (opens in a new tab)
- AAMAS (T1)Probing Dec-POMDP Reasoning in Cooperative MARL (opens in a new tab)
202510 papers
- EurIPS Workshop on Unifying Perspectives on Learning BiasesComputing Strategic Responses to Non-Linear Classifiers (opens in a new tab)
- Foundation and Large Vision Models in Remote Sensing @ CVPRCOP-GEN-Beta: Unified Generative Modelling of COPernicus Imagery Thumbnails (opens in a new tab)
- Stroke and Vascular NeurologyDevelopment of a Deep Learning Method to Identify Acute Ischaemic Stroke Lesions on Brain CT (opens in a new tab)
- ACM Transactions on Architecture and Code OptimizationDLAS: A Conceptual Model for Across-Stack Deep Learning Acceleration (opens in a new tab)
- NeurIPS (T1)HyperMARL: Adaptive Hypernetworks for Multi-Agent RL (opens in a new tab)
- NeurIPS (T1)Is Limited Participant Diversity Impeding EEG-based Machine Learning? (opens in a new tab)
- ICML (T1)Lightweight Online Adaption for Time Series Foundation Model Forecasts (opens in a new tab)
- I Can’t Believe It’s Not Better Workshop @ ICLRPerformance of Zero-Shot Time Series Foundation Models on Cloud Data (opens in a new tab)
- Finding the Frame Workshop @ RLCRemembering the Markov Property in Cooperative MARL (opens in a new tab)
- AutoMLTransferrable Surrogates in Expressive Neural Architecture Search Spaces (opens in a new tab)
202419 papers
- AISTATS (T1)Approximate Bayesian Class-Conditional Models under Continuous Representation Shift (opens in a new tab)
- International Conference on Automated Machine LearningAutomated Prior Elicitation from Large Language Models for Bayesian Logistic Regression (opens in a new tab)
- CoLLAsChunking: Continual Learning is not just about Distribution Shift (opens in a new tab)
- ICLR (T1)DAM: Towards a Foundation Model for Forecasting (opens in a new tab)
- NeurIPS (T1)Diffusion for World Modeling: Visual Details Matter in Atari (opens in a new tab)
- TMI (T1)Diffusion Models for Counterfactual Generation and Anomaly Detection in Brain Images (opens in a new tab)
- ECCV (T1)EgoPoseFormer: A Simple Baseline for Stereo Egocentric 3D Human Pose Estimation (opens in a new tab)
- NeurIPS (T1)einspace: Searching for Neural Architectures from Fundamental Operations (opens in a new tab)
- TMLR (T1)Evaluating the evaluators: Are validation methods for few-shot learning fit for purpose? (opens in a new tab)
- NeurIPS (T1)Generating Compositional Scenes via Text-to-image RGBA Instance Generation (opens in a new tab)
- ICML WorkshopLiouna: Biologically Plausible Learning for Efficient Pre-Training of Transferrable Deep Models (opens in a new tab)
- COLING (T1)LLM-Personalize: Aligning LLM Planners with Human Preferences via Reinforced Self-Training for Housekeeping Robots (opens in a new tab)
202315 papers
- ICML (T1)ACAT: Adversarial Counterfactual Attention for Classification and Detection in Medical Imaging (opens in a new tab)
- AISTATS (T1)Adversarial Robustness of β−VAE Through the Lens of Local Geometry (opens in a new tab)
- ICLR (T1)Amortised Invariance Learning for Contrastive Self-Supervision (opens in a new tab)
- International Journal of Medical InformaticsCan Deep Learning on Retinal Images Augment Known Risk Factors for Cardiovascular Disease Prediction in Diabetes? A Prospective Cohort Study from the National Screening Programme in Scotland (opens in a new tab)
- ICLR (T1)Contrastive Meta-Learning for Partially Observable Few-Shot Learning (opens in a new tab)
- —Deep Learning Detection of Diabetic Retinopathy in Scotland’s Diabetic Eye Screening Programme (opens in a new tab)
- ICLR WorkshopEffectiveness of Debiasing Techniques: An Indigenous Qualitative Analysis (opens in a new tab)
- ICML WorkshopEvaluating the Evaluators: Are Current Few-Shot Learning Benchmarks Fit for Purpose? (opens in a new tab)
- Investigative Ophthalmology & Visual ScienceExclusion of Poor Quality Fundus Images Biases Health Research Linking Retinal Traits and Systemic Health (opens in a new tab)
- NeurIPS WorkshopGenerate Your Own Scotland: Satellite Image Generation Conditioned on Maps (opens in a new tab)
- ICLR (T1)GPViT: A High Resolution Non-Hierarchical Vision Transformer with Group Propagation (opens in a new tab)
- I Can't Believe It's Not Better!Is Scaling Learned Optimizers Worth It? Evaluating The Value of VeLO's 4000 TPU Months (opens in a new tab)
Where alumni went
Alumni are not listed on the lab homepage.
Apply to EdinburghFall 2027
Not announced yet
Informatics PhD
- Round
- Rolling (funding consideration)
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- none
Not yet confirmed for this intake.
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