Sean B. Holden

46 papers A* 7A 1B 2C 3Misc 2Journal 17Unranked 13
YearRankTypeTitle / Venue / Authors
2026 J jnl
WybeCoder: Verified Imperative Code Generation.
CoRR
Fabian Gloeckle, Mantas Baksys, Darius Feher, Kunhao Zheng, Amaury Hayat, Sean B. Holden, Gabriel Synnaeve, Peter W. O'Hearn
2025 J jnl
ContextFlow: Context-Aware Flow Matching For Trajectory Inference From Spatial Omics Data.
CoRR
Santanu Rathod, Francesco Ceccarelli, Sean B. Holden, Pietro Liò, Xiao Zhang, Jovan Tanevski
2025 C conf
Partition Tree Ensembles for Improving Multi-Class Classification.
ICPRAM
Miran Özdogan, Alan Jeffares, Sean B. Holden
2024 C conf
Integrating Structure and Sequence: Protein Graph Embeddings via GNNs and LLMs.
ICPRAM
Francesco Ceccarelli, Lorenzo Giusti, Sean B. Holden, Pietro Liò
2024 B conf
MUGI-MRI: Enhancing Breast Cancer Classification through Multiplex Graph Neural Networks in DCE-MRI.
IJCNN
Francesco Ceccarelli, Francesco Prinzi, Pietro Liò, Salvatore Vitabile, Sean B. Holden
2023 — conf
A Syntax for Connection Proofs.
AReCCa@TABLEAUX
Jens Otten, Sean B. Holden
2023 — conf
Connect++: A New Automated Theorem Prover Based on the Connection Calculus.
AReCCa@TABLEAUX
Sean B. Holden
2023 — conf
Connections: Markov Decision Processes for Classical, Intuitionistic and Modal Connection Calculi.
AReCCa@TABLEAUX
Fredrik Rømming, Jens Otten, Sean B. Holden
2023 J jnl
Neural Embeddings for Protein Graphs.
CoRR
Francesco Ceccarelli, Lorenzo Giusti, Sean B. Holden, Pietro Liò
2022 A conf
Bayesian Ranking for Strategy Scheduling in Automated Theorem Provers.
IJCAR
Chaitanya Mangla, Sean B. Holden, Lawrence C. Paulson
2022 J jnl
Building a 3-Player Mahjong AI using Deep Reinforcement Learning.
CoRR
Xiangyu Zhao, Sean B. Holden
2022 A* conf
On the Relation between Distributionally Robust Optimization and Data Curation (Student Abstract).
AAAI
Agnieszka Slowik, Léon Bottou, Sean B. Holden, Mateja Jamnik
2022 C conf
Towards a Competitive 3-Player Mahjong AI using Deep Reinforcement Learning.
CoG
Xiangyu Zhao, Sean B. Holden
2021 J jnl
Machine Learning for Automated Theorem Proving: Learning to Solve SAT and QSAT.
Found. Trends Mach. Learn.
Sean B. Holden
2021 B conf
Structural Inductive Biases in Emergent Communication.
CogSci
Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden, Chris Pal
2020 A* conf
Bayesian Optimisation for Premise Selection in Automated Theorem Proving (Student Abstract).
AAAI
Agnieszka Slowik, Chaitanya Mangla, Mateja Jamnik, Sean B. Holden, Lawrence C. Paulson
2020 — conf
Bayesian Optimisation of Solver Parameters in CBMC.
SMT
Chaitanya Mangla, Sean B. Holden, Lawrence C. Paulson
2020 J jnl
Exploring Structural Inductive Biases in Emergent Communication.
CoRR
Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden, Christopher J. Pal
2020 J jnl
Towards Graph Representation Learning in Emergent Communication.
CoRR
Agnieszka Slowik, Abhinav Gupta, William L. Hamilton, Mateja Jamnik, Sean B. Holden
2019 — conf
Bayesian Optimisation for Heuristic Configuration in Automated Theorem Proving.
Vampire
Agnieszka Slowik, Chaitanya Mangla, Mateja Jamnik, Sean B. Holden, Lawrence C. Paulson
2019 J jnl
Bayesian Optimisation with Gaussian Processes for Premise Selection.
CoRR
Agnieszka Slowik, Chaitanya Mangla, Mateja Jamnik, Sean B. Holden, Lawrence C. Paulson
2018 J jnl
Co-complex protein membership evaluation using Maximum Entropy on GO ontology and InterPro annotation.
Bioinform.
Irina M. Armean, Kathryn S. Lilley, Matthew W. B. Trotter, Nicholas Charles Victor Pilkington, Sean B. Holden
2016 J jnl
Learning from Heterogeneous Data Sources: An Application in Spatial Proteomics.
PLoS Comput. Biol.
Lisa M. Breckels, Sean B. Holden, David Wojnar, Claire M. Mulvey, Andy Christoforou, Arnoud Groen, Matthew W. B. Trotter, Oliver Kohlbacher, Kathryn S. Lilley, Laurent Gatto
2015 A* conf
Beyond location check-ins: Exploring physical and soft sensing to augment social check-in apps.
PerCom
Kiran K. Rachuri, Theus Hossmann, Cecilia Mascolo, Sean B. Holden
2015 — conf
Learning Dynamic Systems from Time-series Data - An Application to Gene Regulatory Networks.
ICPRAM (2)
Ivo J. P. M. Timóteo, Sean B. Holden
2014 J jnl
Machine Learning for First-Order Theorem Proving - Learning to Select a Good Heuristic.
J. Autom. Reason.
James P. Bridge, Sean B. Holden, Lawrence C. Paulson
2010 A* conf
Handling Goal Utility Dependencies in a Satisfiability Framework.
ICAPS
Richard Anthony Russell, Sean B. Holden
2008 — conf
Modeling the Model Athlete: Automatic Coaching of Rowing Technique.
SSPR/SPR
Simon Fothergill, Robert Harle, Sean B. Holden
2007 — conf
Robust Regression with Twinned Gaussian Processes.
NIPS
Andrew Naish-Guzman, Sean B. Holden
2007 — conf
The Generalized FITC Approximation.
NIPS
Andrew Naish-Guzman, Sean B. Holden
2005 — conf
Bayesian Hierarchical Ordinal Regression.
ICANN (2)
Ulrich Paquet, Sean B. Holden, Andrew Naish-Guzman
2005 — conf
On the Explicit Use of Example Weights in the Construction of Classifiers.
ICANN (2)
Andrew Naish-Guzman, Sean B. Holden, Ulrich Paquet
2002 J jnl
Drug Design by Machine Learning: Support Vector Machines for Pharmaceutical Data Analysis.
Comput. Chem.
Robert Burbidge, Matthew W. B. Trotter, Bernard F. Buxton, Sean B. Holden
2001 — conf
Performance Degradation in Boosting.
Multiple Classifier Systems
Jeevani Wickramaratna, Sean B. Holden, Bernard F. Buxton
2001 — conf
STAR - Sparsity through Automated Rejection.
IWANN (1)
Robert Burbidge, Matthew W. B. Trotter, Bernard F. Buxton, Sean B. Holden
1998 A* conf
Cross-Validation for Binary Classification by Real-Valued Functions: Theoretical Analysis.
COLT
Martin Anthony, Sean B. Holden
1997 J jnl
Average-Case Learning Curves for Radial Basis Function Networks.
Neural Comput.
Sean B. Holden, Mahesan Niranjan
1996 A* conf
PAC-Like Upper Bounds for the Sample Complexity of Leave-one-Out Cross-Validation.
COLT
Sean B. Holden
1995 J jnl
Generalization and PAC learning: some new results for the class of generalized single-layer networks.
IEEE Trans. Neural Networks
Sean B. Holden, Peter J. W. Rayner
1995 J jnl
On the practical applicability of VC dimension bounds.
Neural Comput.
Sean B. Holden, Mahesan Niranjan
1995 J jnl
On the statistical physics of radial basis function networks.
Neural Process. Lett.
Sean B. Holden, Mahesan Niranjan
1994 J jnl
Quantifying Generalization in Linearly Weighted Neural Networks.
Complex Syst.
Martin Anthony, Sean B. Holden
1993 A* conf
On the Power of Polynomial Discriminators and Radial Basis Function Networks.
COLT
Martin Anthony, Sean B. Holden
1993 — —
On the theory of generalization and self-structuring in linearly weighted connectionist networks.
Sean B. Holden
1992 Misc conf
Generalization and learning in Volterra and radial basis function networks: a theoretical analysis.
ICASSP
Sean B. Holden, Peter J. W. Rayner
1991 Misc conf
Removal of degeneracy in adaptive Volterra networks by dynamic structuring.
ICASSP
Michael R. Lynch, Peter J. W. Rayner, Sean B. Holden