Antti Honkela

Juha Karhunen, Antti Honkela, Harri Valpola, 2002, Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290).

An Introduction to Systems Biology from a Machine Learning Perspective II

Neil D. Lawrence, Antti Honkela, Michalis K. Titsias, 2009 .

Gaussian process modelling of latent chemical species: applications to inferring transcription factor activities

Neil D. Lawrence, Antti Honkela, Magnus Rattray, 2008, ECCB.

Privacy-preserving data sharing via probabilistic modelling pdf

Antti Honkela, Sasu Tarkoma, Eemil Lagerspetz, 2019, ArXiv.

Macadamia: Master's Programme in Machine Learning and Data Mining

Erkki Oja, Juha Karhunen, Antti Honkela, 2008 .

Empirical evidence of the linear nature of magnetoencephalograms

Antti Honkela, Ricardo Vigário, Tomas Östman, 2005, ESANN.

Accelerating Cyclic Update Algorithms for Parameter Estimation by Pattern Searches

Juha Karhunen, Antti Honkela, Harri Valpola, 2003, Neural Processing Letters.

Learning rate adaptation for differentially private stochastic gradient descent pdf

Antti Honkela, Antti Koskela, A. Honkela, 2018, ArXiv.

Gaussian process modelling of multiple short time series

Antti Honkela, Hande Topa, 2015, ESANN.

A gradient-based algorithm competitive with variational Bayesian EM for mixture of Gaussians

Juha Karhunen, Antti Honkela, Tapani Raiko, 2009, 2009 International Joint Conference on Neural Networks.

On the inconsistency of ℓ1-penalised sparse precision matrix estimation

Antti Honkela, Janne Leppä-aho, Jukka Corander, 2016, BMC Bioinformatics.

Identifying targets of multiple co-regulating transcription factors from expression time-series by Bayesian model comparison

Neil D. Lawrence, Antti Honkela, Magnus Rattray, 2012, BMC Systems Biology.

prebs User Guide

Antti Honkela, Karolis Uziela, 2016 .

Ranking of gene regulators through differential equations and Gaussian processes

Neil D. Lawrence, Antti Honkela, Magnus Rattray, 2010, 2010 IEEE International Workshop on Machine Learning for Signal Processing.

Using Kernel PCA for Initialisation of Variational Bayesian Nonlinear Blind Source Separation Method

Antti Honkela, Harri Valpola, Stefan Harmeling, 2004 .

Inference of RNA Polymerase II Transcription Dynamics from Chromatin Immunoprecipitation Time Course Data

Neil D. Lawrence, Antti Honkela, Magnus Rattray, 2013, PLoS Comput. Biol..

Differentially private cross-silo federated learning pdf

Antti Honkela, Samuel Kaski, Kana Shimizu, 2020, ArXiv.

High-resolution sweep metagenomics using fast probabilistic inference

Jukka Corander, Antti Honkela, David M. Aanensen, 2018, bioRxiv.

Agglomerative Independent Variable Group Analysis

Antti Honkela, Esa Alhoniemi, Jeremias Seppä, 2007, ESANN.

Computing Tight Differential Privacy Guarantees Using FFT

Antti Honkela, Joonas Jälkö, Antti Koskela, 2020, AISTATS.

Bayesian identification of bacterial strains from sequencing data

Jukka Corander, Antti Honkela, Aravind Sankar, 2015, Microbial genomics.

GPrank: an R package for detecting dynamic elements from genome-wide time series

Antti Honkela, Hande Topa, A. Honkela, 2018, BMC Bioinformatics.

Exploration and retrieval of whole-metagenome sequencing samples

Antti Honkela, Samuel Kaski, Sohan Seth, 2013, Bioinform..

Variational learning and bits-back coding: an information-theoretic view to Bayesian learning

Antti Honkela, Harri Valpola, H. Valpola, 2004, IEEE Transactions on Neural Networks.

Compact Modeling of Data Using Independent Variable Group Analysis

Antti Honkela, Harri Valpola, Paul Wagner, 2007, IEEE Transactions on Neural Networks.

Nonlinear source separation using ensemble learning and MLP networks

Juha Karhunen, Antti Honkela, H. Lappalainen, 2000, Proceedings of the IEEE 2000 Adaptive Systems for Signal Processing, Communications, and Control Symposium (Cat. No.00EX373).

tigre: Transcription factor inference through gaussian process reconstruction of expression for bioconductor

Neil D. Lawrence, Antti Honkela, Magnus Rattray, 2011, Bioinform..

Efficient differentially private learning improves drug sensitivity prediction

Antti Honkela, Samuel Kaski, Onur Dikmen, 2016, Biology Direct.

Differentially Private Bayesian Inference for Generalized Linear Models pdf

Antti Honkela, Joonas Jälkö, Samuel Kaski, 2020, ArXiv.

Identifying differentially expressed transcripts from RNA-seq data with biological variation

Antti Honkela, Magnus Rattray, Peter Glaus, 2011, Bioinform..

Privacy-preserving Data Sharing on Vertically Partitioned Data pdf

Antti Honkela, Joonas Jälkö, Samuel Kaski, 2020, ArXiv.

High-resolution sweep metagenomics using fast probabilistic inference

Antti Honkela, Julian Parkhill, David M. Aanensen, 2020 .

Differentially Private Federated Variational Inference pdf

Antti Honkela, Richard E. Turner, Michael Hutchinson, 2019, ArXiv.

Learning rate adaptation for federated and differentially private learning

Antti Honkela, Antti Koskela, A. Honkela, 2018, 1809.03832.

A Generative Approach for Image-Based Modeling of Tumor Growth

Antti Honkela, Nicholas Ayache, Koenraad Van Leemput, 2011, IPMI.

Time Series Prediction with Variational Bayesian Nonlinear State-Space Models

Juha Karhunen, Antti Honkela, Matti Tornio, 2007 .

Learning Rate Adaptation for Differentially Private Learning

Antti Honkela, Antti Koskela, A. Honkela, 2020, AISTATS.

Differentially Private Markov Chain Monte Carlo

Antti Honkela, Joonas Jälkö, Onur Dikmen, 2019, NeurIPS.

Advances in variational Bayesian nonlinear blind source separation

Antti Honkela, A. Honkela, Antti Honkela, 2005 .

Bayesian Non-Linear Independent Component Analysis by Multi-Layer Perceptrons

Antti Honkela, Harri Lappalainen, A. Honkela, 2000 .

Bayes Blocks Software Library

Antti Honkela, Tapani Raiko, Markus Harva, 2003 .

Proceedings of the 2010 IEEE International Workshop on Machine Learning for Signal Processing (MLSP 2010)

Erkki Oja, Antti Honkela, Samuel Kaski, 2010 .

Analysis of differential splicing suggests different modes of short-term splicing regulation

Antti Honkela, Hande Topa, A. Honkela, 2016, Bioinform..

On-line Variational Bayesian Learning

Antti Honkela, Harri Valpola, H. Valpola, 2003 .

Probe Region Expression Estimation for RNA-Seq Data for Improved Microarray Comparability

Antti Honkela, Karolis Uziela, A. Honkela, 2013, PloS one.

Approximate Riemannian Conjugate Gradient Learning for Fixed-Form Variational Bayes

Juha Karhunen, Antti Honkela, Tapani Raiko, 2010, J. Mach. Learn. Res..

Model-based method for transcription factor target identification with limited data

Antti Honkela, Magnus Rattray, Charles Girardot, 2010, Proceedings of the National Academy of Sciences.

Missing-Feature Reconstruction With a Bounded Nonlinear State-Space Model

Mikko Kurimo, Antti Honkela, Tapani Raiko, 2011, IEEE Signal Processing Letters.

Tight Accounting in the Shuffle Model of Differential Privacy pdf

Antti Honkela, Mikko A. Heikkilä, Antti Koskela, 2021, ArXiv.

Tight Differential Privacy for Discrete-Valued Mechanisms and for the Subsampled Gaussian Mechanism Using FFT

Antti Honkela, Joonas Jälkö, Antti Koskela, 2020, AISTATS.

Locally Differentially Private Bayesian Inference pdf

Antti Honkela, Samuel Kaski, Joonas Jälkö, 2021, ArXiv.

Gaussian Processes with Differential Privacy pdf

Antti Honkela, Antti Honkela, 2021, ArXiv.

d3p - A Python Package for Differentially-Private Probabilistic Programming pdf

Antti Honkela, Samuel Kaski, Lukas Prediger, 2021, ArXiv.

Computing Differential Privacy Guarantees for Heterogeneous Compositions Using FFT pdf

Antti Honkela, Antti Koskela, A. Honkela, 2021, ArXiv.

Differentially Private Hamiltonian Monte Carlo pdf

Antti Honkela, Antti Koskela, Ossi Räisä, 2021, ArXiv.

Differentially Private Bayesian Inference for Generalized Linear Models

Antti Honkela, Joonas Jälkö, Samuel Kaski, 2021, ICML.

Exploration and retrieval of whole-metagenome sequencing

Antti Honkela, Samuel Kaski, Sohan Seth, 2014 .

Variational inference and learning for non-linear state-space models with state-dependent observation noise

Antti Honkela, A. Honkela, V. Peltola, 2010, 2010 IEEE International Workshop on Machine Learning for Signal Processing.

Sequence element enrichment analysis to determine the genetic basis of bacterial phenotypes

Jukka Corander, Antti Honkela, Niko Välimäki, 2016, Nature Communications.

twinify : A software package for differentially private data release

Antti Honkela, Joonas Jälkö, Samuel Kaski, 2020 .

Independent Variable Group Analysis in Learning Compact Representations for Data

Antti Honkela, Esa Alhoniemi, Krista Lagus, 2005 .

Exploring the independence of gene regulatory modules

Antti Honkela, Samuel Kaski, Janne Nikkilä, 2006 .