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Towards Graph Foundation Models for Personalization

2024-05-13 | Conference paper
DOI: 10.1145/3589335.3651980
Contributors: Andreas Damianou; Francesco Fabbri; Paul Gigioli; Marco De Nadai; Alice Wang; Enrico Palumbo; Mounia Lalmas
Source: check_circle
Crossref

Graph Learning for Exploratory Query Suggestions in an Instant Search System

2023-10-21 | Conference paper
DOI: 10.1145/3583780.3615481
Contributors: Enrico Palumbo; Andreas Damianou; Alice Wang; Alva Liu; Ghazal Fazelnia; Francesco Fabbri; Rui Ferreira; Fabrizio Silvestri; Hugues Bouchard; Claudia Hauff et al.
Source: check_circle
Crossref

Efficient Automated Online Experimentation with Multi-Fidelity

Fifth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems
2021 | Conference paper
Contributors: Kleinegesse, Steven; Dai, Zhenwen; Damianou, Andreas; Ciosek, Kamil; Tomasi, Federico
Source: Self-asserted source
Andreas Damianou

Fast adaptation with linearized neural networks

International Conference on Artificial Intelligence and Statistics
2021 | Conference paper
Contributors: Maddox, Wesley; Tang, Shuai; Moreno, Pablo; Wilson, Andrew Gordon; Damianou, Andreas
Source: Self-asserted source
Andreas Damianou

Multi-view Learning as a Nonparametric Nonlinear Inter-Battery Factor Analysis.

Journal of Machine Learning Research (JMLR)
2021 | Journal article
Contributors: Damianou, Andreas C; Lawrence, Neil D; Ek, Carl Henrik
Source: Self-asserted source
Andreas Damianou

Empirical bayes transductive meta-learning with synthetic gradients

International Conference on Learning Representation (ICLR)
2020 | Conference paper
Contributors: Hu, Shell Xu; Moreno, Pablo G; Xiao, Yang; Shen, Xi; Obozinski, Guillaume; Lawrence, Neil D; Damianou, Andreas
Source: Self-asserted source
Andreas Damianou

Online constrained model-based reinforcement learning

Uncertainty in Artificial Intelligence (UAI)
2020 | Conference paper
Contributors: Van Niekerk, Benjamin; Damianou, Andreas; Rosman, Benjamin
Source: Self-asserted source
Andreas Damianou

Similarity of neural networks with gradients

arXiv preprint arXiv:2003.11498
2020 | Journal article
Contributors: Tang, Shuai; Maddox, Wesley J; Dickens, Charlie; Diethe, Tom; Damianou, Andreas
Source: Self-asserted source
Andreas Damianou

Tomographic Auto-Encoder: Unsupervised Bayesian Recovery of Corrupted Data

International Conference on Learning Representations (ICLR)
2020 | Conference paper
Contributors: Tonolini, Francesco; Moreno, Pablo G; Damianou, Andreas; Murray-Smith, Roderick
Source: Self-asserted source
Andreas Damianou

Comprehensive landscape of active deubiquitinating enzymes profiled by advanced chemoproteomics

Frontiers in chemistry
2019 | Journal article
Contributors: Pinto-Fernández, Adán; Davis, Simon; Schofield, Abigail B; Scott, Hannah C; Zhang, Ping; Salah, Eidarus; Mathea, Sebastian; Charles, Philip D; Damianou, Andreas; Bond, Gareth et al.
Source: Self-asserted source
Andreas Damianou

Deep gaussian processes for multi-fidelity modeling

arXiv preprint arXiv:1903.07320
2019 | Journal article
Contributors: Cutajar, Kurt; Pullin, Mark; Damianou, Andreas; Lawrence, Neil; González, Javier
Source: Self-asserted source
Andreas Damianou

Gaussian process introductory tutorial in Python

http://adamian.github.io/talks/Damianou_GP_tutorial.html
2019 | Other
Contributors: Damianou, Andreas
Source: Self-asserted source
Andreas Damianou

Memory and mental time travel in humans and social robots

Philosophical Transactions of the Royal Society B
2019 | Journal article
Contributors: Prescott, Tony J; Camilleri, Daniel; Martinez-Hernandez, Uriel; Damianou, Andreas; Lawrence, Neil D
Source: Self-asserted source
Andreas Damianou

On transfer learning via linearized neural networks

NeurIPS Workshop on Meta-Learning (MetaLearn 2019)
2019 | Conference paper
Contributors: Maddox, Wesley J; Tang, Shuai; Moreno, Pablo Garcia; Wilson, Andrew Gordon; Damianou, Andreas
Source: Self-asserted source
Andreas Damianou

Orl: Reinforcement learning benchmarks for online stochastic optimization problems

arXiv preprint arXiv:1911.10641
2019 | Journal article
Contributors: Balaji, Bharathan; Bell-Masterson, Jordan; Bilgin, Enes; Damianou, Andreas; Garcia, Pablo Moreno; Jain, Arpit; Luo, Runfei; Maggiar, Alvaro; Narayanaswamy, Balakrishnan; Ye, Chun
Source: Self-asserted source
Andreas Damianou

Variational information distillation for knowledge transfer

Proceedings of the IEEE/CVF conference on computer vision and pattern recognition
2019 | Conference paper
Contributors: Ahn, Sungsoo; Hu, Shell Xu; Damianou, Andreas; Lawrence, Neil D; Dai, Zhenwen
Source: Self-asserted source
Andreas Damianou

$β$-BNN: A rate-distortion perspective on Bayesian neural networks

2018 | Journal article
Contributors: Hu, Shell; Damianou, Andreas; Moreno, Pablo Garcia
Source: Self-asserted source
Andreas Damianou

Deep Gaussian processes with convolutional kernels

arXiv preprint arXiv:1806.01655
2018 | Journal article
Contributors: Kumar, Vinayak; Singh, Vaibhav; Srijith, PK; Damianou, Andreas
Source: Self-asserted source
Andreas Damianou

Learn to transfer learn by studying task manifolds

2018 | Journal article
Contributors: Flennerhag, Sebastian; Moreno, Pablo Garcia; Lawrence, Neil; Damianou, Andreas
Source: Self-asserted source
Andreas Damianou

Leveraging crowdsourcing data for deep active learning an application: Learning intents in alexa

Proceedings of the 2018 World Wide Web Conference
2018 | Conference paper
Contributors: Yang, Jie; Drake, Thomas; Damianou, Andreas; Maarek, Yoelle
Source: Self-asserted source
Andreas Damianou

Mutual information guided distillation for transfer learning

2018 | Journal article
Contributors: Ahn, Sung-soo; Hu, Shell; Dai, Zhenwen; Damianou, Andreas; Lawrence, Neil
Source: Self-asserted source
Andreas Damianou

Transferring knowledge across learning processes

International Conference on Learning Representations (ICLR)
2018 | Conference paper
Contributors: Flennerhag, Sebastian; Moreno, Pablo G; Lawrence, Neil D; Damianou, Andreas
Source: Self-asserted source
Andreas Damianou

DAC-h3: a proactive robot cognitive architecture to acquire and express knowledge about the world and the self

IEEE Transactions on Cognitive and Developmental Systems
2017 | Journal article
Contributors: Moulin-Frier, Clément; Fischer, Tobias; Petit, Maxime; Pointeau, Grégoire; Puigbo, Jordi-Ysard; Pattacini, Ugo; Low, Sock Ching; Camilleri, Daniel; Nguyen, Phuong; Hoffmann, Matej et al.
Source: Self-asserted source
Andreas Damianou

Deep recurrent Gaussian processes for outlier-robust system identification

Journal of Process Control
2017 | Journal article
Contributors: Mattos, Cesar Lincoln C; Dai, Zhenwen; Damianou, Andreas; Barreto, Guilherme A; Lawrence, Neil D
Source: Self-asserted source
Andreas Damianou

Manifold Alignment Determination: finding correspondences across different data views

arXiv preprint arXiv:1701.03449
2017 | Journal article
Contributors: Damianou, Andreas; Lawrence, Neil D; Ek, Carl Henrik
Source: Self-asserted source
Andreas Damianou

Nonlinear information fusion algorithms for data-efficient multi-fidelity modelling

Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
2017 | Journal article
Contributors: Perdikaris, Paris; Raissi, Maziar; Damianou, Andreas; Lawrence, Neil D; Karniadakis, George Em
Source: Self-asserted source
Andreas Damianou

Preferential bayesian optimization

International Conference on Machine Learning
2017 | Conference paper
Contributors: González, Javier; Dai, Zhenwen; Damianou, Andreas; Lawrence, Neil D
Source: Self-asserted source
Andreas Damianou

A Bioinspired Approach to Vision

Towards Autonomous Robotic Systems: 17th Annual Conference, TAROS 2016, Sheffield, UK, June 26--July 1, 2016, Proceedings 17
2016 | Conference paper
Contributors: Camilleri, Daniel; Boorman, Luke; Martinez, Uriel; Damianou, Andreas; Prescott, Tony
Source: Self-asserted source
Andreas Damianou

An integrated probabilistic framework for robot perception, learning and memory

2016 IEEE International Conference on Robotics and Biomimetics (ROBIO)
2016 | Conference paper
Contributors: Martinez-Hernandez, Uriel; Damianou, Andreas; Camilleri, Daniel; Boorman, Luke W; Lawrence, Neil; Prescott, Tony J
Source: Self-asserted source
Andreas Damianou

Bayesian optimisation with pairwise preferential returns

NIPS Workshop on Bayesian Optimization
2016 | Conference paper
Contributors: Gonzalez, Javier; Dai, Zhenwen; Damianou, Andreas; Lawrence, Neil D
Source: Self-asserted source
Andreas Damianou

Data Science Africa--An Initiative to Bridge the Data Science Skills Gap in Africa

2016 | Journal article
Contributors: Ciira, Wa Maina
Source: Self-asserted source
Andreas Damianou

iCub visual memory inspector: visualising the iCub’s thoughts

Biomimetic and Biohybrid Systems: 5th International Conference, Living Machines 2016, Edinburgh, UK, July 19-22, 2016. Proceedings 5
2016 | Conference paper
Contributors: Camilleri, Daniel; Damianou, Andreas; Jackson, Harry; Lawrence, Neil; Prescott, Tony
Source: Self-asserted source
Andreas Damianou

Latent autoregressive Gaussian processes models for robust system identification

IFAC-PapersOnLine
2016 | Journal article
Contributors: Mattos, César Lincoln C; Damianou, Andreas; Barreto, Guilherme A; Lawrence, Neil D
Source: Self-asserted source
Andreas Damianou

Probabilistic consolidation of grasp experience

2016 IEEE International Conference on Robotics and Automation (ICRA)
2016 | Conference paper
Contributors: Bekiroglu, Yasemin; Damianou, Andreas; Detry, Renaud; Stork, Johannes A; Kragic, Danica; Ek, Carl Henrik
Source: Self-asserted source
Andreas Damianou

Variational inference for latent variables and uncertain inputs in Gaussian processes

Journal of Machine Learning Research (JMLR)
2016 | Journal article
Contributors: Damianou, Andreas C; Titsias, Michalis K; Lawrence, Neil
Source: Self-asserted source
Andreas Damianou

A top-down approach for a synthetic autobiographical memory system

Biomimetic and Biohybrid Systems: 4th International Conference, Living Machines 2015, Barcelona, Spain, July 28-31, 2015, Proceedings 4
2015 | Conference paper
Contributors: Damianou, Andreas; Ek, Carl Henrik; Boorman, Luke; Lawrence, Neil D; Prescott, Tony J
Source: Self-asserted source
Andreas Damianou

Cognitive architecture for robot perception and learning based on human-robot interaction

IEEE/RSJ IROS Workshops
2015 | Conference paper
Contributors: Martinez-Hernandez, Uriel; Boorman, Luke W; Damianou, Andreas; Prescott, Tony J
Source: Self-asserted source
Andreas Damianou

Deep Gaussian processes and variational propagation of uncertainty

2015 | Dissertation or Thesis
Contributors: Damianou, Andreas
Source: Self-asserted source
Andreas Damianou

Extending a hippocampal model for navigation around a maze generated from real-world data

Biomimetic and Biohybrid Systems: 4th International Conference, Living Machines 2015, Barcelona, Spain, July 28-31, 2015, Proceedings 4
2015 | Conference paper
Contributors: Boorman, Luke W; Damianou, Andreas C; Martinez-Hernandez, Uriel; Prescott, Tony J
Source: Self-asserted source
Andreas Damianou

Inverse reinforcement learning via deep gaussian process

Uncertainty in Artificial Intelligence (UAI)
2015 | Conference paper
Contributors: Jin, Ming; Damianou, Andreas; Abbeel, Pieter; Spanos, Costas
Source: Self-asserted source
Andreas Damianou

Semi-described and semi-supervised learning with Gaussian processes

31st Conference on Uncertainty in Artificial Intelligence (UAI)
2015 | Conference paper
Contributors: Damianou, Andreas; Lawrence, Neil D
Source: Self-asserted source
Andreas Damianou

Variational auto-encoded deep Gaussian processes

International Conference on Learning Representations (ICLR)
2015 | Conference paper
Contributors: Dai, Zhenwen; Damianou, Andreas; González, Javier; Lawrence, Neil
Source: Self-asserted source
Andreas Damianou

Active learning for sparse bayesian multilabel classification

Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining
2014 | Conference paper
Contributors: Vasisht, Deepak; Damianou, Andreas; Varma, Manik; Kapoor, Ashish
Source: Self-asserted source
Andreas Damianou

Deep Gaussian Processes for Large Datasets

AISTATS, late breaking paper
2014 | Conference paper
Contributors: Hensman, James; Damianou, Andreas; Lawrence, Neil
Source: Self-asserted source
Andreas Damianou

Gaussian process models with parallelization and GPU acceleration

NIPS workshop on Software Engineering for Machine Learning
2014 | Conference paper
Contributors: Dai, Zhenwen; Damianou, Andreas; Hensman, James; Lawrence, Neil
Source: Self-asserted source
Andreas Damianou

Uncertainty propagation in Gaussian process pipelines

NIPS workshop on modern non-parametrics
2014 | Conference paper
Contributors: Damianou, A; Lawrence, N
Source: Self-asserted source
Andreas Damianou

Deep Gaussian processes

Proceedings of the Sixteenth International Workshop on Artificial Intelligence and Statistics (AISTATS-13)
2013 | Conference paper
Contributors: C. Damianou, Andreas; D. Lawrence, Neil
Source: Self-asserted source
Andreas Damianou

Factorized Topic Models

International Conference on Learning Representations
2013 | Conference paper
Contributors: Zhang, Cheng; Ek, Carl Henrik; Damianou, Andreas; Kjellstrom, Hedvig
Source: Self-asserted source
Andreas Damianou

Manifold relevance determination

Proceedings of the 29th International Conference on Machine Learning
2012 | Conference paper
Contributors: Damianou, Andreas; Ek, Carl Henrik; Titsias, Michalis; Lawrence, Neil
Source: Self-asserted source
Andreas Damianou

Variational gaussian process dynamical systems

Advances in Neural Information Processing Systems
2011 | Conference paper
Contributors: Damianou, Andreas; Titsias, Michalis K; Lawrence, Neil D
Source: Self-asserted source
Andreas Damianou
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