Neural Networks for Model Matching and Perceptual Organization. - Eric Mjolsness; Gene Gindi; P. Anandan 001 (NIPS, 1988)

Neural network for model based recognition: Simulation results. - Tony Zador; Gene Gindi; Eric Mjolsness; P. Anandan 001 (Neural Networks, 1988)

Optimization in Model Matching and Perceptual Organization. - Eric Mjolsness; Gene Gindi; P. Anandan 001 (Neural Comput., 1989)

Multiscale optimization in neural nets: preliminary report. - Eric Mjolsness; Charles Garrett; Willard L. Miranker (IJCNN, 1990)

A Lagrangian Approach to Fixed Points. - Eric Mjolsness; Willard L. Miranker (NIPS, 1990)

Algebraic transformations of objective functions. - Eric Mjolsness; Charles Garrett (Neural Networks, 1990)

Visual Grammars and Their Neural Nets. - Eric Mjolsness (NIPS, 1991)

Multiscale optimization in neural nets. - Eric Mjolsness; Charles Garrett; Willard L. Miranker (IEEE Trans. Neural Networks, 1991)

Clustering with a Domain-Specific Distance Measure. - Steven Gold; Eric Mjolsness; Anand Rangarajan 001 (NIPS, 1993)

Two-Dimensional Object Localization by Coarse-to-Fine Correlation Matching. - Chien-Ping Lu; Eric Mjolsness (NIPS, 1993)

Animation of plant development. - Przemyslaw Prusinkiewicz; Mark Hammel; Eric Mjolsness (SIGGRAPH, 1993)

Optimization Dynamics for Partitioned Neural Networks. - Dimitris I. Tsioutsias; Eric Mjolsness (Int. J. Neural Syst., 1994)

Modeling the Connection Between Development and Evolution: Preliminary Report. - Eric Mjolsness; Charles Garrett; John Reinitz; David H. Sharp (Evolution and Biocomputation, 1995)

A Mulitscale Attentional Framework for Relaxation Neural Networks. - Dimitris I. Tsioutsias; Eric Mjolsness (NIPS, 1995)

A Convergence Proof for the Softassign Quadratic Assignment Algorithm. - Anand Rangarajan 001; Alan L. Yuille; Steven Gold; Eric Mjolsness (NIPS, 1996)

A Robust Point Matching Algorithm for Autoradiograph Alignment. - Anand Rangarajan 001; Eric Mjolsness; Suguna Pappu; Lila Davachi; Patricia S. Goldman-Rakic; James S. Duncan (VBC, 1996)

A Novel Optimizing Network Architecture with Applications. - Anand Rangarajan 001; Steven Gold; Eric Mjolsness (Neural Comput., 1996)

Learning with Preknowledge: Clustering with Point and Graph Matching Distance Measures. - Steven Gold; Anand Rangarajan 001; Eric Mjolsness (Neural Comput., 1996)

A Lagrangian relaxation network for graph matching. - Anand Rangarajan 001; Eric Mjolsness (IEEE Trans. Neural Networks, 1996)

A robust point-matching algorithm for autoradiograph alignment. - Anand Rangarajan 001; Haili Chui; Eric Mjolsness; Suguna Pappu; Lila Davachi; Patricia S. Goldman-Rakic; James S. Duncan (Medical Image Anal., 1997)

A Langrangian Formulation of Neural Networks, part I: Theory and Analog Dynamics. - Eric Mjolsness; Willard L. Miranker (Neural Parallel Sci. Comput., 1998)

A Langrangian Formulation of Neural Networks, part II: Clocked Objective Functions and Applications. - Eric Mjolsness; Willard L. Miranker (Neural Parallel Sci. Comput., 1998)

New algorithms for 2D and 3D point matching: pose estimation and correspondence. - Steven Gold; Anand Rangarajan 001; Chien-Ping Lu; Suguna Pappu; Eric Mjolsness (Pattern Recognit., 1998)

An Integrated System for Multi-Rover Scientific Exploration. - Tara A. Estlin; Alexander G. Gray; Tobias Mann; Gregg R. Rabideau; Rebecca Castaño; Steve A. Chien; Eric Mjolsness (AAAI/IAAI, 1999)

Morphogenesis in Plants: Modeling the Shoot Apical Meristem, and Possible Applications. - Eric Mjolsness; Elliot M. Meyerowitz; Victoria Gor; Tobias Mann (Evolvable Hardware, 1999)

A New Distance Measure for Non-rigid Image Matching. - Anand Rangarajan 001; Haili Chui; Eric Mjolsness (EMMCVPR, 1999)

From Coexpression to Coregulation: An Approach to Inferring Transcriptional Regulation among Gene Classes from Large-Scale Expression Data. - Eric Mjolsness; Tobias Mann; Rebecca Castaño; Barbara J. Wold (NIPS, 1999)

Convergence Properties of the Softassign Quadratic Assignment Algorithm. - Anand Rangarajan 001; Alan L. Yuille; Eric Mjolsness (Neural Comput., 1999)

The Synergy of Biology, Intelligent Systems, and Space Exploration. - Eric Mjolsness; Ann Tavormina (IEEE Intell. Syst., 2000)

Fast and Globally Convergent Pose Estimation from Video Images. - Chien-Ping Lu; Gregory D. Hager; Eric Mjolsness (IEEE Trans. Pattern Anal. Mach. Intell., 2000)

A Relationship between Spline-Based Deformable Models and Weighted Graphs in Non-Rigid Matching. - Anand Rangarajan 001; Haili Chui; Eric Mjolsness (CVPR (1), 2001)

Goal-Directed Scientific Exploration Using Multiple Rovers. - Tara A. Estlin; Rebecca Castaño; Ashley Davies; Darren Mutz; Gregg R. Rabideau; Steve A. Chien; Eric Mjolsness (FLAIRS, 2001)

Translation-invariant mixture models for curve clustering. - Darya Chudova; Scott Gaffney; Eric Mjolsness; Padhraic Smyth (KDD, 2003)

Gene Expression Clustering with Functional Mixture Models. - Darya Chudova; Christopher E. Hart; Eric Mjolsness; Padhraic Smyth (NIPS, 2003)

The systems biology markup language (SBML): a medium for representation and exchange of biochemical network models. - Michael Hucka; Andrew Finney; Herbert M. Sauro; H. Bolouri; John C. Doyle 001; Hiroaki Kitano; Adam P. Arkin; Benjamin J. Bornstein; Dennis Bray; Athel Cornish-Bowden; Autumn A. Cuellar; Serge Dronov; et al. (Bioinform., 2003)

Cellerator: extending a computer algebra system to include biochemical arrows for signal transduction simulations. - Bruce E. Shapiro; Andre Levchenko; Elliot M. Meyerowitz; Barbara J. Wold; Eric Mjolsness (Bioinform., 2003)

Clustering analysis of microarray gene expression data by splitting algorithm. - Ruye Wang; Lucas Scharenbroich; Christopher E. Hart; Barbara J. Wold; Eric Mjolsness (J. Parallel Distributed Comput., 2003)

Tracking Cell Signals in Fluorescent Images. - Victoria Gor; Michael B. Elowitz; Tigran Bacarian; Eric Mjolsness (CVPR Workshops, 2005)

Modeling the organization of the WUSCHEL expression domain in the shoot apical meristem. - Henrik Jönsson; Marcus Heisler; G. Venugopala Reddy; Vikas Agrawal; Victoria Gor; Bruce E. Shapiro; Eric Mjolsness; Elliot M. Meyerowitz (ISMB (Supplement of Bioinformatics), 2005)

An enzyme mechanism language for the mathematical modeling of metabolic pathways. - Chin-Rang Yang; Bruce E. Shapiro; Eric Mjolsness; G. Wesley Hatfield (Bioinform., 2005)

Sigmoid: A Software Infrastructure for Pathway Bioinformatics and Systems Biology. - Jianlin Cheng; Lucas Scharenbroich; Pierre Baldi; Eric Mjolsness (IEEE Intell. Syst., 2005)

Stochastic Process Semantics for Dynamical Grammar Syntax: An Overview. - Eric Mjolsness (AI&M, 2006)

Stochastic process semantics for dynamical grammars. - Eric Mjolsness; Guy Yosiphon (Ann. Math. Artif. Intell., 2006)

Static and dynamic models of biological networks. - Ashish Bhan; Eric Mjolsness (Complex., 2006)

Application of a Generalized Mwc Model for the Mathematical Simulation of Metabolic Pathways Regulated by Allosteric Enzymes. - Tarek S. Najdi; Chin-Rang Yang; Bruce E. Shapiro; G. Wesley Hatfield; Eric Mjolsness (J. Bioinform. Comput. Biol., 2006)

Towards learned traversability for robot navigation: From underfoot to the far field. - Andrew Howard; Michael J. Turmon; Larry H. Matthies; Benyang Tang; Anelia Angelova; Eric Mjolsness (J. Field Robotics, 2006)

Connectivity in the Yeast Cell Cycle Transcription Network: Inferences from Neural Networks. - Christopher E. Hart; Eric Mjolsness; Barbara J. Wold (PLoS Comput. Biol., 2006)

From Published Expression and Phenotype Data to Structured Knowledge: The Arabidopsis Gene Net Supplementary Database and Its Applications. - Denis K. Ponomaryov; Nadezhda Omelianchuk; Victoria V. Mironova; Eugene Zalevsky; Nikolay L. Podkolodny; Eric Mjolsness; Nikolay A. Kolchanov (KONT/KPP, 2007)

Towards a calculus of biomolecular complexes at equilibrium. - Eric Mjolsness (Briefings Bioinform., 2007)

On Cooperative Quasi-Equilibrium Models of transcriptional Regulation. - Eric Mjolsness (J. Bioinform. Comput. Biol., 2007)

Toward the Inference of Stochastic Biochemical Network and Parameterized Grammar Models. - Guy Yosiphon; Eric Mjolsness (Learning and Inference in Computational Systems Biology, 2010)

A plausible mechanism for auxin patterning along the developing root. - Victoria V. Mironova; Nadezda A. Omelyanchuk; Guy Yosiphon; Stanislav I. Fadeev; Nikolay A. Kolchanov; Eric Mjolsness; Vitali A. Likhoshvai (BMC Syst. Biol., 2010)

Parameter inference for discretely observed stochastic kinetic models using stochastic gradient descent. - Yuanfeng Wang; Scott Christley; Eric Mjolsness; Xiaohui Xie (BMC Syst. Biol., 2010)

Towards Measurable Types for Dynamical Process Modeling Languages. - Eric Mjolsness (MFPS, 2010)

Time-Ordered Product Expansions for Computational Stochastic Systems Biology - Eric Mjolsness (CoRR, 2012)

Compositional Stochastic Modeling and Probabilistic Programming - Eric Mjolsness (CoRR, 2012)

A Hierarchical Exact Accelerated Stochastic Simulation Algorithm - David Orendorff; Eric Mjolsness (CoRR, 2012)

Quantitative Symbolic Process Models: How a Fair Fraction of Intelligence Could Be Abstracted in AI Research. - Eric Mjolsness (AAAI Fall Symposia, 2013)

Pycellerator: an arrow-based reaction-like modelling language for biological simulations. - Bruce E. Shapiro; Eric Mjolsness (Bioinform., 2016)

Prospects for Declarative Mathematical Modeling of Complex Biological Systems. - Eric Mjolsness (CoRR, 2018)

Deep Learning Moment Closure Approximations using Dynamic Boltzmann Distributions. - Oliver K. Ernst; Tom Bartol; Terrence J. Sejnowski; Eric Mjolsness (CoRR, 2019)

Structural Commutation Relations for Stochastic Labelled Graph Grammar Rule Operators. - Eric Mjolsness (CoRR, 2019)

Novel diffusion-derived distance measures for graphs. - Cory B. Scott; Eric Mjolsness (CoRR, 2019)

Multilevel Artificial Neural Network Training for Spatially Correlated Learning. - Cory B. Scott; Eric Mjolsness (SIAM J. Sci. Comput., 2019)

Graph Prolongation Convolutional Networks: Explicitly Multiscale Machine Learning on Graphs, with Applications to Modeling of Biological Systems. - Cory B. Scott; Eric Mjolsness (CoRR, 2020)

Diff2Dist: Learning Spectrally Distinct Edge Functions, with Applications to Cell Morphology Analysis. - Cory Braker Scott; Eric Mjolsness; Diane Oyen; Chie Kodera; David Bouchez; Magalie Uyttewaal (CoRR, 2021)

Physics-based machine learning for modeling stochastic IP3-dependent calcium dynamics. - Oliver K. Ernst; Tom Bartol; Terrence J. Sejnowski; Eric Mjolsness (CoRR, 2021)

Graph prolongation convolutional networks: explicitly multiscale machine learning on graphs with applications to modeling of cytoskeleton. - Cory B. Scott; Eric Mjolsness (Mach. Learn. Sci. Technol., 2021)

Feynman on Artificial Intelligence and Machine Learning, with Updates. - Eric Mjolsness (CoRR, 2022)

Graph Lineages and Skeletal Graph Products. - Eric Mjolsness; Cory B. Scott (CoRR, 2025)