Manfred Opper

2008
35	EE	Manfred Opper, Ulrich Paquet, Ole Winther: Improving on Expectation Propagation. NIPS 2008: 1241-1248
2007
34	EE	Cédric Archambeau, Manfred Opper, Yuan Shen, Dan Cornford, John Shawe-Taylor: Variational Inference for Diffusion Processes. NIPS 2007
33	EE	Manfred Opper, Guido Sanguinetti: Variational inference for Markov jump processes. NIPS 2007
2005
32	EE	Manfred Opper: An Approximate Inference Approach for the PCA Reconstruction Error. NIPS 2005
31	EE	Manfred Opper, Ole Winther: Expectation Consistent Approximate Inference. Journal of Machine Learning Research 6: 2177-2204 (2005)
2004
30	EE	Manfred Opper, Ole Winther: Approximate Inference in Probabilistic Models. ALT 2004: 494-504
29	EE	Manfred Opper, Ole Winther: Expectation Consistent Free Energies for Approximate Inference. NIPS 2004
2003
28	EE	Dörthe Malzahn, Manfred Opper: Approximate Analytical Bootstrap Averages for Support Vector Classifiers. NIPS 2003
27	EE	Manfred Opper, Ole Winther: Variational Linear Response. NIPS 2003
26	EE	Dörthe Malzahn, Manfred Opper: Learning curves and bootstrap estimates for inference with Gaussian processes: A statistical mechanics study. Complexity 8(4): 57-63 (2003)
25	EE	Lehel Csató, Manfred Opper, Ole Winther: Tractable inference for probabilistic data models. Complexity 8(4): 64-68 (2003)
24	EE	Dörthe Malzahn, Manfred Opper: An Approximate Analytical Approach to Resampling Averages. Journal of Machine Learning Research 4: 1151-1173 (2003)
2002
23	EE	Dörthe Malzahn, Manfred Opper: A Statistical Mechanics Approach to Approximate Analytical Bootstrap Averages. NIPS 2002: 327-334
22	EE	Yoav Freund, Manfred Opper: Drifting Games and Brownian Motion. J. Comput. Syst. Sci. 64(1): 113-132 (2002)
21	EE	Lehel Csató, Manfred Opper: Sparse On-Line Gaussian Processes. Neural Computation 14(3): 641-668 (2002)
2001
20	EE	Dörthe Malzahn, Manfred Opper: Learning Curves for Gaussian Processes Models: Fluctuations and Universality. ICANN 2001: 271-276
19	EE	Lehel Csató, Dan Cornford, Manfred Opper: Online Approximations for Wind-Field Models. ICANN 2001: 300-307
18	EE	Dörthe Malzahn, Manfred Opper: A Variational Approach to Learning Curves. NIPS 2001: 463-469
17	EE	Manfred Opper, Robert Urbanczik: Asymptotic Universality for Learning Curves of Support Vector Machines. NIPS 2001: 479-486
16	EE	Lehel Csató, Manfred Opper, Ole Winther: TAP Gibbs Free Energy, Belief Propagation and Sparsity. NIPS 2001: 657-663
2000
15		Yoav Freund, Manfred Opper: Continuous Drifting Games. COLT 2000: 126-132
14		Dörthe Malzahn, Manfred Opper: Learning Curves for Gaussian Processes Regression: A Framework for Good Approximations. NIPS 2000: 273-279
13		Lehel Csató, Manfred Opper: Sparse Representation for Gaussian Process Models. NIPS 2000: 444-450
12		Manfred Opper, Ole Winther: Gaussian Processes for Classification: Mean-Field Algorithms. Neural Computation 12(11): 2655-2684 (2000)
1999
11	EE	Lehel Csató, Ernest Fokoué, Manfred Opper, Bernhard Schottky, Ole Winther: Efficient Approaches to Gaussian Process Classification. NIPS 1999: 251-257
1998
10	EE	Giancarlo Ferrari-Trecate, Christopher K. I. Williams, Manfred Opper: Finite-Dimensional Approximation of Gaussian Processes. NIPS 1998: 218-224
9	EE	Manfred Opper, Francesco Vivarelli: General Bounds on Bayes Errors for Regression with Gaussian Processes. NIPS 1998: 302-308
8	EE	Manfred Opper, Ole Winther: Mean Field Methods for Classification with Gaussian Processes. NIPS 1998: 309-315
1997
7		David Haussler, Manfred Opper: Metric Entropy and Minimax Risk in Classification. Structures in Logic and Computer Science 1997: 212-235
1996
6	EE	Siegfried Bös, Manfred Opper: Dynamics of Training. NIPS 1996: 141-147
5	EE	Manfred Opper, Ole Winther: A Mean Field Algorithm for Bayes Learning in Large Feed-forward Neural Networks. NIPS 1996: 225-231
1995
4	EE	David Haussler, Manfred Opper: General Bounds on the Mutual Information Between a Parameter and n Conditionally Independent Observations. COLT 1995: 402-411
1992
3	EE	H. Sebastian Seung, Manfred Opper, Haim Sompolinsky: Query by Committee. COLT 1992: 287-294
1991
2	EE	Manfred Opper, David Haussler: Calculation of the Learning Curve of Bayes Optimal Classification Algorithm for Learning a Perceptron With Noise. COLT 1991: 75-87
1	EE	David Haussler, Michael J. Kearns, Manfred Opper, Robert E. Schapire: Estimating Average-Case Learning Curves Using Bayesian, Statistical Physics and VC Dimension Methods. NIPS 1991: 855-862

Coauthor Index

1	Cédric Archambeau	[34]
2	Siegfried Bös	[6]
3	Dan Cornford	[19] [34]
4	Lehel Csató	[11] [13] [16] [19] [21] [25]
5	Giancarlo Ferrari-Trecate	[10]
6	Ernest Fokoué	[11]
7	Yoav Freund	[15] [22]
8	David Haussler	[1] [2] [4] [7]
9	Michael J. Kearns	[1]
10	Dörthe Malzahn	[14] [18] [20] [23] [24] [26] [28]
11	Ulrich Paquet	[35]
12	Guido Sanguinetti	[33]
13	Robert E. Schapire	[1]
14	Bernhard Schottky	[11]
15	H. Sebastian Seung	[3]
16	John Shawe-Taylor	[34]
17	Yuan Shen	[34]
18	Haim Sompolinsky	[3]
19	Robert Urbanczik	[17]
20	Francesco Vivarelli	[9]
21	Christopher K. I. Williams	[10]
22	Ole Winther	[5] [8] [11] [12] [16] [25] [27] [29] [30] [31] [35]

Colors in the list of coauthors