David Barber

2008
31	EE	David Barber: Clique Matrices for Statistical Graph Decomposition and Parameterising Restricted Positive Definite Matrices. UAI 2008: 26-33
2007
30	EE	Bertrand Mesot, David Barber: Switching Linear Dynamical Systems for Noise Robust Speech Recognition. IEEE Transactions on Audio, Speech & Language Processing 15(6): 1850-1858 (2007)
2006
29	EE	Mike Perrow, David Barber: Tagging of name records for genealogical data browsing. JCDL 2006: 316-325
28	EE	David Barber, Silvia Chiappa: Unified Inference for Variational Bayesian Linear Gaussian State-Space Models. NIPS 2006: 81-88
27	EE	David Barber, Bertrand Mesot: A Novel Gaussian Sum Smoother for Approximate Inference in Switching Linear Dynamical Systems. NIPS 2006: 89-96
26	EE	David Barber: Expectation Correction for Smoothed Inference in Switching Linear Dynamical Systems. Journal of Machine Learning Research 7: 2515-2540 (2006)
25	EE	Jean-Pascal Pfister, Taro Toyoizumi, David Barber, Wulfram Gerstner: Optimal Spike-Timing-Dependent Plasticity for Precise Action Potential Firing in Supervised Learning. Neural Computation 18(6): 1318-1348 (2006)
24	EE	Silvia Chiappa, David Barber: EEG classification using generative independent component analysis. Neurocomputing 69(7-9): 769-777 (2006)
2005
23	EE	Silvia Chiappa, David Barber: generative independent component analysis for EEG classification. ESANN 2005: 297-302
22	EE	Jean-François Paiement, Douglas Eck, Samy Bengio, David Barber: A graphical model for chord progressions embedded in a psychoacoustic space. ICML 2005: 641-648
21	EE	Felix V. Agakov, David Barber: Kernelized Infomax Clustering. NIPS 2005
20	EE	Felix V. Agakov, David Barber: Auxiliary Variational Information Maximization for Dimensionality Reduction. SLSFS 2005: 103-114
2004
19	EE	Felix V. Agakov, David Barber: Variational Information Maximization for Neural Coding. ICONIP 2004: 543-548
18	EE	Felix V. Agakov, David Barber: An Auxiliary Variational Method. ICONIP 2004: 561-566
2003
17	EE	Felix V. Agakov, David Barber: Approximate Learning in Temporal Hidden Hopfield Models. ICANN 2003: 107-114
16	EE	Jean-Pascal Pfister, David Barber, Wulfram Gerstner: Optimal Hebbian Learning: A Probabilistic Point of View. ICANN 2003: 92-98
15	EE	David Barber, Felix V. Agakov: The IM Algorithm: A Variational Approach to Information Maximization. NIPS 2003
2002
14	EE	David Barber: Learning in Spiking Neural Assemblies. NIPS 2002: 149-156
13	EE	David Barber: Dynamic Bayesian Networks with Deterministic Latent Tables. NIPS 2002: 713-720
2001
12		Machiel Westerdijk, David Barber, Wim Wiegerinck: Deterministic Generative Models for Fast Feature Discovery. Data Min. Knowl. Discov. 5(4): 337-363 (2001)
1999
11	EE	David Barber, Peter Sollich: Gaussian Fields for Approximate Inference in Layered Sigmoid Belief Networks. NIPS 1999: 393-399
10	EE	David Barber, Piërre van de Laar: Variational Cumulant Expansions for Intractable Distributions. J. Artif. Intell. Res. (JAIR) 10: 435-455 (1999)
1998
9	EE	David Barber, Wim Wiegerinck: Tractable Variational Structures for Approximating Graphical Models. NIPS 1998: 183-189
8	EE	Christopher K. I. Williams, David Barber: Bayesian Classification With Gaussian Processes. IEEE Trans. Pattern Anal. Mach. Intell. 20(12): 1342-1351 (1998)
7		Peter Sollich, David Barber: Online Learning from Finite Training Sets and Robustness to Input Bias. Neural Computation 10(8): 2201-2217 (1998)
1997
6		David Barber, Christopher M. Bishop: Ensemble Learning for Multi-Layer Networks. NIPS 1997
5		Peter Sollich, David Barber: On-line Learning from Finite Training Sets in Nonlinear Networks. NIPS 1997
4		David Barber, Bernhard Schottky: Radial Basis Functions: A Bayesian Treatment. NIPS 1997
1996
3	EE	Peter Sollich, David Barber: Online Learning from Finite Training Sets: An Analytical Case Study. NIPS 1996: 274-280
2	EE	David Barber, Christopher M. Bishop: Bayesian Model Comparison by Monte Carlo Chaining. NIPS 1996: 333-339
1	EE	David Barber, Christopher K. I. Williams: Gaussian Processes for Bayesian Classification via Hybrid Monte Carlo. NIPS 1996: 340-346

Coauthor Index

1	Felix V. Agakov	[15] [17] [18] [19] [20] [21]
2	Samy Bengio	[22]
3	Christopher M. Bishop	[2] [6]
4	Silvia Chiappa	[23] [24] [28]
5	Douglas Eck	[22]
6	Wulfram Gerstner	[16] [25]
7	Piërre van de Laar	[10]
8	Bertrand Mesot	[27] [30]
9	Jean-François Paiement	[22]
10	Mike Perrow	[29]
11	Jean-Pascal Pfister	[16] [25]
12	Bernhard Schottky	[4]
13	Peter Sollich	[3] [5] [7] [11]
14	Taro Toyoizumi	[25]
15	Machiel Westerdijk	[12]
16	Wim Wiegerinck	[9] [12]
17	Christopher K. I. Williams	[1] [8]

Colors in the list of coauthors