Andreas C. Damianou

45 papers A* 10A 5Journal 23Unranked 7

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