Peter Sollich - RankMe

54 papers A 1B 4Misc 1Journal 22Unranked 25

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Physics-inspired machine learning detects 'unknown unknowns' in networks: discovering network boundaries from observable dynamics. Mach. Learn. Sci. Technol. Moshir Harsh, Leonhard Götz Vulpius, Peter Sollich
2022	J	`jnl`	Towards Robust Waveform-Based Acoustic Models. IEEE ACM Trans. Audio Speech Lang. Process. Dino Oglic, Zoran Cvetkovic, Peter Sollich, Steve Renals, Bin Yu
2021	J	`jnl`	Learning Waveform-Based Acoustic Models Using Deep Variational Convolutional Neural Networks. IEEE ACM Trans. Audio Speech Lang. Process. Dino Oglic, Zoran Cvetkovic, Peter Sollich
2021	J	`jnl`	Towards Robust Waveform-Based Acoustic Models. CoRR Dino Oglic, Zoran Cvetkovic, Peter Sollich, Steve Renals, Bin Yu
2020	J	`jnl`	Nonlinear memory functions capture and explain dynamical behaviours. CoRR Edgar Herrera-Delgado, James Briscoe, Peter Sollich
2019	J	`jnl`	Parzen Filters for Spectral Decomposition of Signals. CoRR Dino Oglic, Zoran Cvetkovic, Peter Sollich
2018	J	`jnl`	Memory functions reveal structural properties of gene regulatory networks. PLoS Comput. Biol. Edgar Herrera-Delgado, Ruben Perez-Carrasco, James Briscoe, Peter Sollich
2017	J	`jnl`	Dynamical selection of Nash equilibria using Experience Weighted Attraction Learning: emergence of heterogeneous mixed equilibria. CoRR Robin Nicole, Peter Sollich
2017	J	`jnl`	Phase Diagram of Restricted Boltzmann Machines and Generalised Hopfield Networks with Arbitrary Priors. CoRR Adriano Barra, Giuseppe Genovese, Daniele Tantari, Peter Sollich
2016	J	`jnl`	Phase transitions in Restricted Boltzmann Machines with generic priors. CoRR Adriano Barra, Giuseppe Genovese, Peter Sollich, Daniele Tantari
2014	J	`jnl`	A Subband-Based SVM Front-End for Robust ASR. CoRR Jibran Yousafzai, Zoran Cvetkovic, Peter Sollich, Matthew Ager
2013	—	`conf`	Effects of domain-specific SVM kernel design on the robustness of automatic speech recognition. DSP Jibran Yousafzai, Zoran Cvetkovic, Peter Sollich
2013	J	`jnl`	Phoneme Classification in High-Dimensional Linear Feature Domains. CoRR Matthew Ager, Zoran Cvetkovic, Peter Sollich
2013	J	`jnl`	Random walk kernels and learning curves for Gaussian process regression on random graphs. J. Mach. Learn. Res. Matthew Urry, Peter Sollich
2012	J	`jnl`	Learning curves for multi-task Gaussian process regression CoRR Simon R. F. Ashton, Peter Sollich
2012	—	`conf`	Learning curves for multi-task Gaussian process regression. NIPS Peter Sollich, Simon R. F. Ashton
2012	J	`jnl`	Random walk kernels and learning curves for Gaussian process regression on random graphs CoRR Matthew Urry, Peter Sollich
2011	J	`jnl`	Combined Features and Kernel Design for Noise Robust Phoneme Classification Using Support Vector Machines. IEEE Trans. Speech Audio Process. Jibran Yousafzai, Peter Sollich, Zoran Cvetkovic, Bin Yu
2011	B	`conf`	Combined waveform-cepstral representation for robust speech recognition. ISIT Matthew Ager, Zoran Cvetkovic, Peter Sollich
2010	—	`conf`	Exact learning curves for Gaussian process regression on large random graphs. NIPS Matthew Urry, Peter Sollich
2010	Misc	`conf`	High-dimensional linear representations for robust speech recognition. ITA Matthew Ager, Zoran Cvetkovic, Peter Sollich
2010	—	`conf`	Subband acoustic waveform front-end for robust speech recognition using support vector machines. SLT Jibran Yousafzai, Zoran Cvetkovic, Peter Sollich
2010	B	`conf`	Towards robust phoneme classification with hybrid features. ISIT Jibran Yousafzai, Zoran Cvetkovic, Peter Sollich
2009	—	`conf`	Custom-designed SVM kernels for improved robustness of phoneme classification. EUSIPCO Jibran Yousafzai, Zoran Cvetkovic, Peter Sollich
2009	—	`conf`	Kernels and learning curves for Gaussian process regression on random graphs. NIPS Peter Sollich, Matthew Urry, Camille Coti
2009	—	`conf`	Robust phoneme classification: Exploiting the adaptability of acoustic waveform models. EUSIPCO Matthew Ager, Zoran Cvetkovic, Peter Sollich
2009	A	`conf`	Tuning support vector machines for robust phoneme classification with acoustic waveforms. INTERSPEECH Jibran Yousafzai, Zoran Cvetkovic, Peter Sollich
2008	—	`conf`	Combined PLP - Acoustic waveform classification for robust phoneme recognition using support vector machines. EUSIPCO Jibran Yousafzai, Zoran Cvetkovic, Peter Sollich, Bin Yu
2008	—	`conf`	Towards robust phoneme classification: Augmentation of PLP models with acoustic waveforms. EUSIPCO Matthew Ager, Zoran Cvetkovic, Peter Sollich, Bin Yu
2007	—	`conf`	Phoneme Classification in Frequency Subbands using Ensemble Methods. DSP Nicholas Betteridge, Zoran Cvetkovic, Peter Sollich
2007	—	`conf`	Stable Belief Propagation in Gaussian Dags. ICASSP (2) David Barber, Peter Sollich
2006	—	`conf`	Robustness of phoneme classification in different representation spaces. EUSIPCO Lena Khoo, Zoran Cvetkovic, Peter Sollich
2005	J	`jnl`	Bayesian approach to feature selection and parameter tuning for support vector machine classifiers. Neural Networks Carl Gold, Alex Holub, Peter Sollich
2005	B	`conf`	Fast Bayesian support vector machine parameter tuning with the Nystrom method. IJCNN Carl Gold, Peter Sollich
2004	—	`conf`	Can Gaussian Process Regression Be Made Robust Against Model Mismatch? Deterministic and Statistical Methods in Machine Learning Peter Sollich
2004	—	`conf`	Understanding Gaussian Process Regression Using the Equivalent Kernel. Deterministic and Statistical Methods in Machine Learning Peter Sollich, Christopher K. I. Williams
2004	—	`conf`	Using the Equivalent Kernel to Understand Gaussian Process Regression. NIPS Peter Sollich, Christopher K. I. Williams
2003	J	`jnl`	Model selection for support vector machine classification. Neurocomputing Carl Gold, Peter Sollich
2002	J	`jnl`	Bayesian Methods for Support Vector Machines: Evidence and Predictive Class Probabilities. Mach. Learn. Peter Sollich
2002	J	`jnl`	Learning Curves for Gaussian Process Regression: Approximations and Bounds. Neural Comput. Peter Sollich, Anason S. Halees
2001	—	`conf`	Gaussian Process Regression with Mismatched Models. NIPS Peter Sollich
1999	—	`conf`	Gaussian Fields for Approximate Inference in Layered Sigmoid Belief Networks. NIPS David Barber, Peter Sollich
1999	—	`conf`	Probabilistic Methods for Support Vector Machines. NIPS Peter Sollich
1998	—	`conf`	Learning Curves for Gaussian Processes. NIPS Peter Sollich
1998	—	`conf`	On-Line Learning with Restricted Training Sets: Exact Solution as Benchmark for General Theories. NIPS H. C. Rae, Peter Sollich, Anthony C. C. Coolen
1998	J	`jnl`	Online Learning from Finite Training Sets and Robustness to Input Bias. Neural Comput. Peter Sollich, David Barber
1997	—	`conf`	On-line Learning from Finite Training Sets in Nonlinear Networks. NIPS Peter Sollich, David Barber
1996	—	`conf`	Online Learning from Finite Training Sets: An Analytical Case Study. NIPS Peter Sollich, David Barber
1995	—	`—`	Asking intelligent questions : the statistical mechanics of query learning. Peter Sollich
1995	—	`conf`	Learning with ensembles: How overfitting can be useful. NIPS Peter Sollich, Anders Krogh
1995	B	`conf`	Minimum entropy queries for linear students learning nonlinear rules. ESANN Peter Sollich
1995	J	`jnl`	Test Error Fluctuations in Finite Linear Perceptrons. Neural Comput. David Barber, David Saad, Peter Sollich
1994	—	`conf`	Learning from queries for maximum information gain in imperfectly learnable problems. NIPS Peter Sollich, David Saad
1994	—	`conf`	Learning in large linear perceptrons and why the thermodynamic limit is relevant to the real world. NIPS Peter Sollich