Publications (34)
Efficient Bayesian Inference of Sigmoidal Gaussian Cox Processes
Christian Donner, Manfred Opper
Approximate Bayes learning of stochastic differential equations
Philipp Batz, Andreas Ruttor, Manfred Opper
Dynamical Functional Theory for Compressed Sensing
Burak Ãakmak, Manfred Opper, Ole Winther +1
Perturbative Black Box Variational Inference
Robert Bamler, Cheng Zhang, Manfred Opper +1
Variational perturbation and extended Plefka approaches to dynamics on random networks: the case of the kinetic Ising model
Ludovica Bachschmid-Romano, Claudia Battistin, Manfred Opper +1
Efficient Gaussian Process Classification Using Polya-Gamma Data Augmentation
Florian Wenzel, Theo Galy-Fajou, Christan Donner +2
Visualizing the Effects of a Changing Distance on Data Using Continuous Embeddings
Gina Gruenhage, Manfred Opper, Simon Barthelme
Efficient statistical inference for stochastic reaction processes
Andreas Ruttor, Manfred Opper
Statistical Mechanics of Learning in the Presence of Outliers
Rainer Dietrich, Manfred Opper
Efficient Bayesian Inference for a Gaussian Process Density Model
Christian Donner, Manfred Opper
Learning of couplings for random asymmetric kinetic Ising models revisited: random correlation matrices and learning curves
Ludovica Bachschmid-Romano, Manfred Opper
Expectation Propagation
Jack Raymond, Andre Manoel, Manfred Opper
An analytically tractable model of neural population activity in the presence of common input explains higher-order correlations and entropy
Jakob H Macke, Manfred Opper, Matthias Bethge
Statistical Mechanics of Support Vector Networks
Rainer Dietrich, Manfred Opper, Haim Sompolinsky
Perturbative Corrections for Approximate Inference in Gaussian Latent Variable Models
Manfred Opper, Ulrich Paquet, Ole Winther
Inferring hidden states in a random kinetic Ising model: replica analysis
Ludovica Bachschmid Romano, Manfred Opper
Multi-Class Gaussian Process Classification Made Conjugate: Efficient Inference via Data Augmentation
Théo Galy-Fajou, Florian Wenzel, Christian Donner +1
Memory-free dynamics for the TAP equations of Ising models with arbitrary rotation invariant ensembles of random coupling matrices
Burak Ãakmak, Manfred Opper
Dynamic State Estimation Based on Poisson Spike Trains: Towards a Theory of Optimal Encoding
Alex Susemihl, Ron Meir, Manfred Opper
Extended Plefka Expansion for Stochastic Dynamics
Barbara Bravi, Peter Sollich, Manfred Opper
Temporal Autoencoding Improves Generative Models of Time Series
Chris Häusler, Alex Susemihl, Martin P Nawrot +1
Tractable approximations for probabilistic models: The adaptive TAP mean field approach
Manfred Opper, Ole Winther
Optimal Encoding and Decoding for Point Process Observations: an Approximate Closed-Form Filter
Yuval Harel, Ron Meir, Manfred Opper
A Theory of Solving TAP Equations for Ising Models with General Invariant Random Matrices
Manfred Opper, Burak Ãakmak, Ole Winther
A statistical physics approach to learning curves for the Inverse Ising problem
Ludovica Bachschmid-Romano, Manfred Opper
Expectation propagation for continuous time stochastic processes
Botond Cseke, David Schnoerr, Manfred Opper +1
Inferring hidden states in Langevin dynamics on large networks: Average case performance
Barbara Bravi, Manfred Opper, Peter Sollich
Optimal decoding of dynamic stimuli encoded by heterogeneous populations of spiking neurons - a closed form approximation
Yuval Harel, Ron Meir, Manfred Opper
Variational estimation of the drift for stochastic differential equations from the empirical density
Philipp Batz, Andreas Ruttor, Manfred Opper
Optimal Population Codes for Control and Estimation
Alex Susemihl, Ron Meir, Manfred Opper
Self-Averaging Expectation Propagation
Burak Ãakmak, Manfred Opper, Bernard H. Fleury +1
An Analytically Tractable Bayesian Approximation to Optimal Point Process Filtering
Yuval Harel, Ron Meir, Manfred Opper
Expectation Propagation for Approximate Inference: Free Probability Framework
Burak Ãakmak, Manfred Opper
Inverse Ising problem in continuous time: A latent variable approach
Christian Donner, Manfred Opper