On the short-term-memory of WTA nets. - Brijnesh J. Jain; Fritz Wysotzki (ESANN, 2001)

Efficient Pattern Discrimination with Inhibitory WTA Nets. - Brijnesh J. Jain; Fritz Wysotzki (ICANN, 2001)

Fast Winner-Takes-All Networks for the Maximum Clique Problem. - Brijnesh J. Jain; Fritz Wysotzki (KI, 2002)

A Neural Graph Isomorphism Algorithm based on local Invariants. - Brijnesh J. Jain; Fritz Wysotzki (ESANN, 2003)

An Associative Memory for the Automorphism Group of Structures. - Brijnesh J. Jain; Fritz Wysotzki (ESANN, 2003)

A Competitive Winner-Takes-All Architecture for Classification and Pattern Recognition of Structures. - Brijnesh J. Jain; Fritz Wysotzki (GbRPR, 2003)

A Novel Neural Network Approach to Solve Exact and Inexact Graph Isomorphism Problems. - Brijnesh J. Jain; Fritz Wysotzki (ICANN, 2003)

Perceptron learning in the domain of graphs. - Brijnesh J. Jain; Fritz Wysotzki (IJCNN, 2003)

A k-Winner-Takes-All Classifier for Structured Data. - Brijnesh J. Jain; Fritz Wysotzki (KI, 2003)

Automorphism Partitioning with Neural Networks. - Brijnesh J. Jain; Fritz Wysotzki (Neural Process. Lett., 2003)

SVM learning with the SH inner product. - Peter Geibel; Brijnesh J. Jain; Fritz Wysotzki (ESANN, 2004)

Neural methods for non-standard data. - Barbara Hammer; Brijnesh J. Jain (ESANN, 2004)

The maximum weighted clique problem and Hopfield networks. - Brijnesh J. Jain; Fritz Wysotzki (ESANN, 2004)

Multi-layer perceptron learning in the domain of attributed graphs. - Brijnesh J. Jain; Fritz Wysotzki (IJCNN, 2004)

Combining Recurrent Neural Networks and Support Vector Machines for Structural Pattern Recognition. - Brijnesh J. Jain; Peter Geibel; Fritz Wysotzki (KI, 2004)

Learning with Neural Networks in the Domain of Graphs. - Brijnesh J. Jain; Fritz Wysotzki (LWA, 2004)

Structural Perceptrons for Attributed Graphs. - Brijnesh J. Jain; Fritz Wysotzki (SSPR/SPR, 2004)

Central Clustering of Attributed Graphs. - Brijnesh J. Jain; Fritz Wysotzki (Mach. Learn., 2004)

Discrimination networks for maximum selection. - Brijnesh J. Jain; Fritz Wysotzki (Neural Networks, 2004)

Structural Neuronal Learning Machines. - Brijnesh Johannes Jain (Ausgezeichnete Informatikdissertationen, 2005)

SVM learning with the Schur-Hadamard inner product for graphs. - Brijnesh J. Jain; Peter Geibel; Fritz Wysotzki (Neurocomputing, 2005)

Solving inexact graph isomorphism problems using neural networks. - Brijnesh J. Jain; Fritz Wysotzki (Neurocomputing, 2005)

Structural neural learning machines. - Brijnesh Johannes Jain (2005)

Joining Softassign and Dynamic Programming for the Contact Map Overlap Problem. - Brijnesh J. Jain; Michael Lappe (BIRD, 2007)

On the sample mean of graphs. - Brijnesh J. Jain; Klaus Obermayer (IJCNN, 2008)

Molecule Kernels: A Descriptor- and Alignment-Free Quantitative Structure-Activity Relationship Approach. - Johannes Mohr; Brijnesh J. Jain; Klaus Obermayer (J. Chem. Inf. Model., 2008)

Algorithms for the Sample Mean of Graphs. - Brijnesh J. Jain; Klaus Obermayer (CAIP, 2009)

Bimal: Bipartite matching alignment for the contact map overlap problem. - Brijnesh J. Jain; Klaus Obermayer (IJCNN, 2009)

Multiple alignment of contact maps. - Brijnesh J. Jain; Brijnesh Stehr; Michael Lappe; Klaus Obermayer (IJCNN, 2009)

A Necessary and Sufficient Condition for Graph Matching Being Equivalent to the Maximum Weight Clique Problem - Brijnesh J. Jain; Klaus Obermayer (CoRR, 2009)

Elkan's k-Means for Graphs - Brijnesh J. Jain; Klaus Obermayer (CoRR, 2009)

Structure Spaces. - Brijnesh J. Jain; Klaus Obermayer (J. Mach. Learn. Res., 2009)

Consistent Estimator of Median and Mean Graph. - Brijnesh J. Jain; Klaus Obermayer (ICPR, 2010)

Elkan's k-Means Algorithm for Graphs. - Brijnesh J. Jain; Klaus Obermayer (MICAI (2), 2010)

Large Sample Statistics in the Domain of Graphs. - Brijnesh J. Jain; Klaus Obermayer (SSPR/SPR, 2010)

Learning Graph Quantization. - Brijnesh J. Jain; S. Deepak Srinivasan; Alexander Tissen; Klaus Obermayer (SSPR/SPR, 2010)

Accelerating Competitive Learning Graph Quantization - Brijnesh J. Jain; Klaus Obermayer (CoRR, 2010)

A Maximum Common Subgraph Kernel Method for Predicting the Chromosome Aberration Test. - Johannes Mohr; Brijnesh J. Jain; Andreas Sutter; Antonius ter Laak; Thomas Steger-Hartmann; Nikolaus Heinrich; Klaus Obermayer (J. Chem. Inf. Model., 2010)

Pattern recognition in multivariate time series: dissertation proposal. - Stephan Spiegel; Brijnesh Johannes Jain; Ernesto William De Luca; Sahin Albayrak (PIKM@CIKM, 2011)

Maximum Likelihood for Gaussians on Graphs. - Brijnesh J. Jain; Klaus Obermayer (GbRPR, 2011)

Generalized Learning Graph Quantization. - Brijnesh J. Jain; Klaus Obermayer (GbRPR, 2011)

Extending Bron Kerbosch for Solving the Maximum Weight Clique Problem - Brijnesh J. Jain; Klaus Obermayer (CoRR, 2011)

Graph quantization. - Brijnesh J. Jain; Klaus Obermayer (Comput. Vis. Image Underst., 2011)

Correlating perception-oriented aspects in user-centric recommender system evaluation. - Alan Said; Brijnesh J. Jain; Andreas Lommatzsch; Sahin Albayrak (IIiX, 2012)

KMulE: a framework for user-based comparison of recommender algorithms. - Alan Said; Ernesto William De Luca; Benjamin Kille; Brijnesh J. Jain; Immo Micus; Sahin Albayrak (IUI, 2012)

Analyzing weighting schemes in collaborative filtering: cold start, post cold start and power users. - Alan Said; Brijnesh J. Jain; Sahin Albayrak (SAC, 2012)

Estimating the magic barrier of recommender systems: a user study. - Alan Said; Brijnesh J. Jain; Sascha Narr; Till Plumbaum; Sahin Albayrak; Christian Scheel (SIGIR, 2012)

Users and Noise: The Magic Barrier of Recommender Systems. - Alan Said; Brijnesh J. Jain; Sascha Narr; Till Plumbaum (UMAP, 2012)

Learning in Riemannian Orbifolds - Brijnesh J. Jain; Klaus Obermayer (CoRR, 2012)

Maximum likelihood method for parameter estimation of bell-shaped functions on graphs. - Brijnesh J. Jain (Pattern Recognit. Lett., 2012)

Mixtures of Radial Densities for Clustering Graphs. - Brijnesh J. Jain (CAIP (1), 2013)

User-centric evaluation of a K-furthest neighbor collaborative filtering recommender algorithm. - Alan Said; Ben Fields; Brijnesh J. Jain; Sahin Albayrak (CSCW, 2013)

A 3D approach to recommender system evaluation. - Alan Said; Brijnesh J. Jain; Sahin Albayrak (CSCW Companion, 2013)

Margin Perceptrons for Graphs. - Brijnesh J. Jain (ICPR, 2014)

Users' reading habits in online news portals. - Cagdas Esiyok; Benjamin Kille; Brijnesh Johannes Jain; Frank Hopfgartner; Sahin Albayrak (IIiX, 2014)

Fast time series classification under lucky time warping distance. - Stephan Spiegel; Brijnesh Johannes Jain; Sahin Albayrak (SAC, 2014)

Flip-Flop Sublinear Models for Graphs. - Brijnesh J. Jain (S+SSPR, 2014)

Sublinear Models for Graphs. - Brijnesh J. Jain (CoRR, 2014)

Flip-Flop Sublinear Models for Graphs: Proof of Theorem 1. - Brijnesh J. Jain (CoRR, 2014)

The Gamification Design Problem. - Michael Meder; Brijnesh Johannes Jain (CoRR, 2014)

Time Series Classification in Dissimilarity Spaces. - Brijnesh J. Jain; Stephan Spiegel (AALTD@PKDD/ECML, 2015)

Dimension Reduction in Dissimilarity Spaces for Time Series Classification. - Brijnesh J. Jain; Stephan Spiegel (AALTD@PKDD/ECML (Revised Selected Papers), 2015)

Generalized Gradient Learning on Time Series under Elastic Transformations. - Brijnesh J. Jain (CoRR, 2015)

Geometry of Graph Edit Distance Spaces. - Brijnesh J. Jain (CoRR, 2015)

Properties of the Sample Mean in Graph Spaces and the Majorize-Minimize-Mean Algorithm. - Brijnesh J. Jain (CoRR, 2015)

Asymptotic Behavior of Mean Partitions in Consensus Clustering. - Brijnesh J. Jain (CoRR, 2015)

Generalized gradient learning on time series. - Brijnesh J. Jain (Mach. Learn., 2015)

Homogeneity of Cluster Ensembles. - Brijnesh J. Jain (CoRR, 2016)

A Reduction Theorem for the Sample Mean in Dynamic Time Warping Spaces. - Brijnesh J. Jain; David Schultz (CoRR, 2016)

On the geometry of graph spaces. - Brijnesh J. Jain (Discret. Appl. Math., 2016)

Statistical graph space analysis. - Brijnesh J. Jain (Pattern Recognit., 2016)

Optimal Warping Paths are unique for almost every pair of Time Series. - Brijnesh J. Jain; David Schultz (CoRR, 2017)

Warped-Linear Models for Time Series Classification. - Brijnesh J. Jain (CoRR, 2017)

Consistency of mean partitions in consensus clustering. - Brijnesh J. Jain (Pattern Recognit., 2017)

Condorcet's Jury Theorem for Consensus Clustering. - Brijnesh J. Jain (KI, 2018)

Gamification in E-Commerce: Tangible vs. Intangible Rewards. - Michael Meder; Till Plumbaum; Aleksander Raczkowski; Brijnesh J. Jain; Sahin Albayrak (MindTrek, 2018)

Semi-Metrification of the Dynamic Time Warping Distance. - Brijnesh J. Jain (CoRR, 2018)

The Mean Partition Theorem in consensus clustering. - Brijnesh J. Jain (Pattern Recognit., 2018)

Asymmetric learning vector quantization for efficient nearest neighbor classification in dynamic time warping spaces. - Brijnesh J. Jain; David Schultz (Pattern Recognit., 2018)

Nonsmooth analysis and subgradient methods for averaging in dynamic time warping spaces. - David Schultz; Brijnesh J. Jain (Pattern Recognit., 2018)

Exact mean computation in dynamic time warping spaces. - Markus Brill; Till Fluschnik; Vincent Froese; Brijnesh J. Jain; Rolf Niedermeier; David Schultz (Data Min. Knowl. Discov., 2019)

Making the dynamic time warping distance warping-invariant. - Brijnesh J. Jain (Pattern Recognit., 2019)

Revisiting inaccuracies of time series averaging under dynamic time warping. - Brijnesh J. Jain (Pattern Recognit. Lett., 2019)

Sufficient conditions for the existence of a sample mean of time series under dynamic time warping. - Brijnesh J. Jain; David Schultz (Ann. Math. Artif. Intell., 2020)

Comparing temporal graphs using dynamic time warping. - Vincent Froese; Brijnesh J. Jain; Rolf Niedermeier; Malte Renken (Soc. Netw. Anal. Min., 2020)

Warped softmax regression for time series classification. - Brijnesh J. Jain (Knowl. Inf. Syst., 2021)

Fast Exact Dynamic Time Warping on Run-Length Encoded Time Series. - Vincent Froese; Brijnesh J. Jain; Maciej Rymar; Mathias Weller (Algorithmica, 2023)

When algorithm selection meets Bi-linear Learning to Rank: accuracy and inference time trade off with candidates expansion. - Jing Yuan; Christian Geißler; Weijia Shao; Andreas Lommatzsch; Brijnesh J. Jain (Int. J. Data Sci. Anal., 2023)

An average-compress algorithm for the sample mean problem under dynamic time warping. - Brijnesh J. Jain; Vincent Froese; David Schultz (J. Glob. Optim., 2023)