Tom Heskes

	2009
47		Rasa Jurgelenaite, Tjeerd Dijkstra, Clemens H. M. Kocken, Tom Heskes: Gene regulation in the intraerythrocytic cycle of Plasmodium falciparum. Bioinformatics 25(12): 1484-1491 (2009)
	2008
46		Botond Cseke, Tom Heskes: Bounds on the Bethe Free Energy for Gaussian Networks. UAI 2008: 97-104
	2007
45		José Miguel Hernández-Lobato, Tjeerd Dijkstra, Tom Heskes: Regulator Discovery from Gene Expression Time Series of Malaria Parasites: a Hierachical Approach. NIPS 2007
44		Adriana Birlutiu, Tom Heskes: Expectation Propagation for Rating Players in Sports Competitions. PKDD 2007: 374-381
43		Marcel van Gerven, Rasa Jurgelenaite, Babs G. Taal, Tom Heskes, Peter J. F. Lucas: Predicting carcinoid heart disease with the noisy-threshold classifier. Artificial Intelligence in Medicine 40(1): 45-55 (2007)
42		Bart Bakker, Tom Heskes: Learning and approximate inference in dynamic hierarchical models. Computational Statistics & Data Analysis 52(2): 821-839 (2007)
	2006
41		Rasa Jurgelenaite, Tom Heskes: EM Algorithm for Symmetric Causal Independence Models. ECML 2006: 234-245
40		Rasa Jurgelenaite, Tom Heskes: Symmetric Causal Independence Models for Classification. Probabilistic Graphical Models 2006: 163-170
39		Tom Heskes: Convexity Arguments for Efficient Minimization of the Bethe and Kikuchi Free Energies. J. Artif. Intell. Res. (JAIR) 26: 153-190 (2006)
38		Onno Zoeter, Tom Heskes: Deterministic approximate inference techniques for conditionally Gaussian state space models. Statistics and Computing 16(3): 279-292 (2006)
	2005
37		Tom Heskes, Bert de Vries: Incremental Utility Elicitation for Adaptive Personalization. BNAIC 2005: 127-134
36		Rasa Jurgelenaite, Peter J. F. Lucas, Tom Heskes: Use of the Noisy Threshold Function in Building Bayesian Networks. BNAIC 2005: 158-165
35		Onno Zoeter, Tom Heskes: Gaussian Quadrature Based Expectation Propagation. BNAIC 2005: 407
34		Onno Zoeter, Tom Heskes: Change Point Problems in Linear Dynamical Systems. Journal of Machine Learning Research 6: 1999-2026 (2005)
33		Alexander Ypma, Tom Heskes: Novel approximations for inference in nonlinear dynamical systems using expectation propagation. Neurocomputing 69(1-3): 85-99 (2005)
	2004
32		Alexander Ypma, Tom Heskes: Novel approximations for inference and learning in nonlinear dynamical systems. ESANN 2004: 361-366
31		Tom Heskes: On the Uniqueness of Loopy Belief Propagation Fixed Points. Neural Computation 16(11): 2379-2413 (2004)
	2003
30		Onno Zoeter, Tom Heskes: Multi-scale Switching Linear Dynamical Systems. ICANN 2003: 562-572
29		Tom Heskes, Onno Zoeter, Wim Wiegerinck: Approximate Expectation Maximization. NIPS 2003
28		Tom Heskes, Kees Albers, Bert Kappen: Approximate Inference and Constrained Optimization. UAI 2003: 313-320
27		Onno Zoeter, Tom Heskes: Hierarchical Visualization of Time-Series Data Using Switching Linear Dynamical Systems. IEEE Trans. Pattern Anal. Mach. Intell. 25(10): 1202-1214 (2003)
26		Bart Bakker, Tom Heskes: Task Clustering and Gating for Bayesian Multitask Learning. Journal of Machine Learning Research 4: 83-99 (2003)
25		Tom Heskes, Jan-Joost Spanjers, Bart Bakker, Wim Wiegerinck: Optimising newspaper sales using neural-Bayesian technology. Neural Computing and Applications 12(3-4): 212-219 (2003)
24		Bart Bakker, Tom Heskes: Clustering ensembles of neural network models. Neural Networks 16(2): 261-269 (2003)
	2002
23		Bart Bakker, Tom Heskes: Model Clustering for Neural Network Ensembles. ICANN 2002: 383-388
22		Tom Heskes: Stable Fixed Points of Loopy Belief Propagation Are Local Minima of the Bethe Free Energy. NIPS 2002: 343-350
21		Wim Wiegerinck, Tom Heskes: Fractional Belief Propagation. NIPS 2002: 438-445
20		Tom Heskes, Onno Zoeter: Expectation Propogation for Approximate Inference in Dynamic Bayesian Networks. UAI 2002: 216-223
19		Wim Wiegerinck, Tom Heskes: IPF for Discrete Chain Factor Graphs. UAI 2002: 560-567
18		Alexander Ypma, Tom Heskes: Automatic Categorization of Web Pages and User Clustering with Mixtures of Hidden Markov Models. WEBKDD 2002: 35-49
17		Tom Heskes, Bart Bakker, Bert Kappen: Approximate algorithms for neural-Bayesian approaches. Theor. Comput. Sci. 287(1): 219-238 (2002)
	2000
16		Tom Heskes: Empirical Bayes for Learning to Learn. ICML 2000: 367-374
15		Jakob Vogdrup Hansen, Tom Heskes: General Bias/Variance Decomposition with Target Independent Variance of Error Functions Derived from the Exponential Family of Distributions. ICPR 2000: 2207-2210
14		Tom Heskes, Jan-Joost Spanjers, Wim Wiegerinck: EM Algorithms for Self-Organizing Maps. IJCNN (6) 2000: 9-14
13		Tom Heskes: On "Natural" Learning and Pruning in Multilayered Perceptrons. Neural Computation 12(4): 881-901 (2000)
12		Piërre van de Laar, Tom Heskes: Input selection based on an ensemble. Neurocomputing 34(1-4): 227-238 (2000)
	1999
11		Bart Bakker, Tom Heskes: Model clustering by deterministic annealing. ESANN 1999: 87-92
10		Piërre van de Laar, Tom Heskes, Stan C. A. M. Gielen: Partial Retraining: A New Approach to Input Relevance Determination. Int. J. Neural Syst. 9(1): 75-85 (1999)
9		Piërre van de Laar, Tom Heskes: Pruning Using Parameter and Neuronal Metrics. Neural Computation 11(4): 977-993 (1999)
	1998
8		Tom Heskes: Solving a Huge Number of Similar Tasks: A Combination of Multi-Task Learning and a Hierarchical Bayesian Approach. ICML 1998: 233-241
7		Tom Heskes: Bias/Variance Decompositions for Likelihood-Based Estimators. Neural Computation 10(6): 1425-1433 (1998)
	1997
6		Piërre van de Laar, Stan C. A. M. Gielen, Tom Heskes: Input Selection with Partial Retraining. ICANN 1997: 469-474
5		Tom Heskes: Selecting Weighting Factors in Logarithmic Opinion Pools. NIPS 1997
4		Piërre van de Laar, Tom Heskes, Stan C. A. M. Gielen: Task-Dependent Learning of Attention. Neural Networks 10(6): 981-992 (1997)
	1996
3		Tom Heskes: Practical Confidence and Prediction Intervals. NIPS 1996: 176-182
2		Tom Heskes: Balancing Between Bagging and Bumping. NIPS 1996: 466-472
	1992
1		Tom Heskes, Stan C. A. M. Gielen: Retrieval of pattern sequences at variable speeds in a neural network with delays. Neural Networks 5(1): 145-152 (1992)

Coauthor Index

1	Kees Albers	[28]
2	Bart Bakker	[11] [17] [23] [24] [25] [26] [42]
3	Adriana Birlutiu	[44]
4	Botond Cseke	[46]
5	Tjeerd Dijkstra	[45] [47]
6	Marcel van Gerven	[43]
7	Stan C. A. M. Gielen	[1] [4] [6] [10]
8	Jakob Vogdrup Hansen	[15]
9	José Miguel Hernández-Lobato	[45]
10	Rasa Jurgelenaite	[36] [40] [41] [43] [47]
11	Bert Kappen	[17] [28]
12	Clemens H. M. Kocken	[47]
13	Piërre van de Laar	[4] [6] [9] [10] [12]
14	Peter J. F. Lucas	[36] [43]
15	Jan-Joost Spanjers	[14] [25]
16	Babs G. Taal	[43]
17	Bert de Vries	[37]
18	Wim Wiegerinck	[14] [19] [21] [25] [29]
19	Alexander Ypma	[18] [32] [33]
20	Onno Zoeter	[20] [27] [29] [30] [34] [35] [38]

Colors in the list of coauthors