Andreas C. Damianou

Publication Activity (10 Years)

Years Active: 2011-2021
Publications (10 Years): 32

Top Topics

Multilabel Classification

Gaussian Process

Reinforcement Learning

Variational Inference

Top Venues

Living Machines

Publications

Francesco Tonolini, Pablo Garcia Moreno, Andreas C. Damianou, Roderick Murray-Smith
Tomographic Auto-Encoder: Unsupervised Bayesian Recovery of Corrupted Data. ICLR (2021)
Wesley J. Maddox, Shuai Tang, Pablo Garcia Moreno, Andrew Gordon Wilson, Andreas C. Damianou
Fast Adaptation with Linearized Neural Networks. CoRR (2021)
Wesley Maddox, Shuai Tang, Pablo Garcia Moreno, Andrew Gordon Wilson, Andreas C. Damianou
Fast Adaptation with Linearized Neural Networks. AISTATS (2021)
Andreas C. Damianou, Neil D. Lawrence, Carl Henrik Ek
Multi-view Learning as a Nonparametric Nonlinear Inter-Battery Factor Analysis. J. Mach. Learn. Res. 22 (2021)
Francesco Tonolini, Pablo Garcia Moreno, Andreas C. Damianou, Roderick Murray-Smith
Tomographic Auto-Encoder: Unsupervised Bayesian Recovery of Corrupted Data. CoRR (2020)
Shuai Tang, Wesley J. Maddox, Charlie Dickens, Tom Diethe, Andreas C. Damianou
Similarity of Neural Networks with Gradients. CoRR (2020)
Shell Xu Hu, Pablo Garcia Moreno, Yang Xiao, Xi Shen, Guillaume Obozinski, Neil D. Lawrence, Andreas C. Damianou
Empirical Bayes Transductive Meta-Learning with Synthetic Gradients. ICLR (2020)
Shell Xu Hu, Pablo Garcia Moreno, Yang Xiao, Xi Shen, Guillaume Obozinski, Neil D. Lawrence, Andreas C. Damianou
Empirical Bayes Transductive Meta-Learning with Synthetic Gradients. CoRR (2020)
Benjamin van Niekerk, Andreas C. Damianou, Benjamin Rosman
Online Constrained Model-based Reinforcement Learning. CoRR (2020)
Kurt Cutajar, Mark Pullin, Andreas C. Damianou, Neil D. Lawrence, Javier González
Deep Gaussian Processes for Multi-fidelity Modeling. CoRR (2019)
Sebastian Flennerhag, Pablo Garcia Moreno, Neil D. Lawrence, Andreas C. Damianou
Transferring Knowledge across Learning Processes. ICLR (2019)
Sungsoo Ahn, Shell Xu Hu, Andreas C. Damianou, Neil D. Lawrence, Zhenwen Dai
Variational Information Distillation for Knowledge Transfer. CVPR (2019)
Sungsoo Ahn, Shell Xu Hu, Andreas C. Damianou, Neil D. Lawrence, Zhenwen Dai
Variational Information Distillation for Knowledge Transfer. CoRR (2019)
Bharathan Balaji, Jordan Bell-Masterson, Enes Bilgin, Andreas C. Damianou, Pablo Moreno Garcia, Arpit Jain, Runfei Luo, Alvaro Maggiar, Balakrishnan Narayanaswamy, Chun Ye
ORL: Reinforcement Learning Benchmarks for Online Stochastic Optimization Problems. CoRR (2019)
Clément Moulin-Frier, Tobias Fischer, Maxime Petit, Grégoire Pointeau, Jordi-Ysard Puigbo, Ugo Pattacini, Sock Ching Low, Daniel Camilleri, Phuong D. H. Nguyen, Matej Hoffmann, Hyung Jin Chang, Martina Zambelli, Anne-Laure Mealier, Andreas C. Damianou, Giorgio Metta, Tony J. Prescott, Yiannis Demiris, Peter Ford Dominey, Paul F. M. J. Verschure
DAC-h3: A Proactive Robot Cognitive Architecture to Acquire and Express Knowledge About the World and the Self. IEEE Trans. Cogn. Dev. Syst. 10 (4) (2018)
Jie Yang, Thomas Drake, Andreas C. Damianou, Yoelle Maarek
Leveraging Crowdsourcing Data for Deep Active Learning An Application: Learning Intents in Alexa. WWW (2018)
Sebastian Flennerhag, Pablo Garcia Moreno, Neil D. Lawrence, Andreas C. Damianou
Transferring Knowledge across Learning Processes. CoRR (2018)
Jie Yang, Thomas Drake, Andreas C. Damianou, Yoelle Maarek
Leveraging Crowdsourcing Data For Deep Active Learning - An Application: Learning Intents in Alexa. CoRR (2018)
Vinayak Kumar, Vaibhav Singh, P. K. Srijith, Andreas C. Damianou
Deep Gaussian Processes with Convolutional Kernels. CoRR (2018)
Javier González, Zhenwen Dai, Andreas C. Damianou, Neil D. Lawrence
Preferential Bayesian Optimization. ICML (2017)
Clément Moulin-Frier, Tobias Fischer, Maxime Petit, Grégoire Pointeau, Jordi-Ysard Puigbo, Ugo Pattacini, Sock Ching Low, Daniel Camilleri, Phuong D. H. Nguyen, Matej Hoffmann, Hyung Jin Chang, Martina Zambelli, Anne-Laure Mealier, Andreas C. Damianou, Giorgio Metta, Tony J. Prescott, Yiannis Demiris, Peter Ford Dominey, Paul F. M. J. Verschure
DAC-h3: A Proactive Robot Cognitive Architecture to Acquire and Express Knowledge About the World and the Self. CoRR (2017)
Andreas C. Damianou, Neil D. Lawrence, Carl Henrik Ek
Manifold Alignment Determination: finding correspondences across different data views. CoRR (2017)
Ming Jin, Andreas C. Damianou, Pieter Abbeel, Costas J. Spanos
Inverse Reinforcement Learning via Deep Gaussian Process. UAI (2017)
Benjamin van Niekerk, Andreas C. Damianou, Benjamin Rosman
Online Constrained Model-based Reinforcement Learning. UAI (2017)
Daniel Camilleri, Luke W. Boorman, Uriel Martinez-Hernandez, Andreas C. Damianou, Tony J. Prescott
A Bioinspired Approach to Vision. TAROS (2016)
Daniel Camilleri, Andreas C. Damianou, Harry Jackson, Neil D. Lawrence, Tony J. Prescott
iCub Visual Memory Inspector: Visualising the iCub's Thoughts. Living Machines (2016)
Uriel Martinez-Hernandez, Andreas C. Damianou, Daniel Camilleri, Luke W. Boorman, Neil D. Lawrence, Tony J. Prescott
An integrated probabilistic framework for robot perception, learning and memory. ROBIO (2016)
Andreas C. Damianou, Neil D. Lawrence, Carl Henrik Ek
Multi-view Learning as a Nonparametric Nonlinear Inter-Battery Factor Analysis. CoRR (2016)
Yasemin Bekiroglu, Andreas C. Damianou, Renaud Detry, Johannes A. Stork, Danica Kragic, Carl Henrik Ek
Probabilistic consolidation of grasp experience. ICRA (2016)
Andreas C. Damianou, Michalis K. Titsias, Neil D. Lawrence
Variational Inference for Latent Variables and Uncertain Inputs in Gaussian Processes. J. Mach. Learn. Res. 17 (2016)
César Lincoln C. Mattos, Zhenwen Dai, Andreas C. Damianou, Jeremy Forth, Guilherme A. Barreto, Neil D. Lawrence
Recurrent Gaussian Processes. ICLR (Poster) (2016)
Zhenwen Dai, Andreas C. Damianou, Javier González, Neil D. Lawrence
Variational Auto-encoded Deep Gaussian Processes. ICLR (Poster) (2016)
Luke W. Boorman, Andreas C. Damianou, Uriel Martinez-Hernandez, Tony J. Prescott
Extending a Hippocampal Model for Navigation Around a Maze Generated from Real-World Data. Living Machines (2015)
Andreas C. Damianou, Carl Henrik Ek, Luke Boorman, Neil D. Lawrence, Tony J. Prescott
A Top-Down Approach for a Synthetic Autobiographical Memory System. Living Machines (2015)
Andreas C. Damianou, Neil D. Lawrence
Semi-described and semi-supervised learning with Gaussian processes. UAI (2015)
Andreas C. Damianou, Neil D. Lawrence
Semi-described and semi-supervised learning with Gaussian processes. CoRR (2015)
Zhenwen Dai, Andreas C. Damianou, James Hensman, Neil D. Lawrence
Gaussian Process Models with Parallelization and GPU acceleration. CoRR (2014)
Andreas C. Damianou, Michalis K. Titsias, Neil D. Lawrence
Variational Inference for Uncertainty on the Inputs of Gaussian Process Models. CoRR (2014)
Deepak Vasisht, Andreas C. Damianou, Manik Varma, Ashish Kapoor
Active learning for sparse bayesian multilabel classification. KDD (2014)
Andreas C. Damianou, Neil D. Lawrence
Deep Gaussian Processes. AISTATS (2013)
Andreas C. Damianou, Carl Henrik Ek, Michalis K. Titsias, Neil D. Lawrence
Manifold Relevance Determination CoRR (2012)
Andreas C. Damianou, Neil D. Lawrence
Deep Gaussian Processes CoRR (2012)
Andreas C. Damianou, Carl Henrik Ek, Michalis K. Titsias, Neil D. Lawrence
Manifold Relevance Determination. ICML (2012)
Andreas C. Damianou, Michalis K. Titsias, Neil D. Lawrence
Variational Gaussian Process Dynamical Systems CoRR (2011)
Andreas C. Damianou, Michalis K. Titsias, Neil D. Lawrence
Variational Gaussian Process Dynamical Systems. NIPS (2011)