Helsinki ICT research is widely represented in the NeurIPS 2020 conference

An impressive set of papers from Helsinki was again this year accepted to the Conference on Neural Information Processing Systems NeurIPS.

In total, the conference has accepted fourteen submissions from either Aalto University or the University of Helsinki. NeurIPS is the largest and most prestigious conference on machine learning.  NeurIPS 2020 will be held entirely online on December 6.-12. 2020. NeurIPS 2019 was held in Vancouver.

Accepted papers from Aalto University and the University of Helsinki:

Robust, Accurate Stochastic Optimization for Variational Inference
Akash Kumar Dhaka (Aalto University) · Alejandro Catalina (Aalto University) · Michael Andersen (Aalto University) · Måns Magnusson (Aalto University) · Jonathan Huggins (Boston University) · Aki Vehtari (Aalto University)

Training Generative Adversarial Networks with Limited Data
Tero Karras (NVIDIA) · Miika Aittala (MIT CSAIL / NVIDIA) · Janne Hellsten (NVIDIA) · Samuli Laine (NVIDIA) · Jaakko Lehtinen (Aalto University & NVIDIA) · Timo Aila (NVIDIA)

Stationary Activations for Uncertainty Calibration in Deep Learning
Lassi Meronen (Aalto University) · Christabella Irwanto (Aalto University) · Arno Solin (Aalto University)

GANSpace: Discovering Interpretable GAN Controls
Erik Härkönen (Aalto University) · Aaron Hertzmann (Adobe) · Jaakko Lehtinen (Aalto University & NVIDIA) · Sylvain Paris (Adobe)

Deep Automodulators
Ari Heljakka (Aalto University) · Yuxin Hou (Aalto University) · Juho Kannala (Aalto University) · Arno Solin (Aalto University)

Discovering conflicting groups in signed networks
Ruo-Chun Tzeng (KTH) · Bruno Ordozgoiti (Aalto University) · Aristides Gionis (KTH Royal Institute of Technology)

Hamiltonian Monte Carlo using an adjoint-differentiated Laplace approximation
Charles Margossian (Columbia) · Aki Vehtari (Aalto University) · Daniel Simpson (University of Toronto) · Raj Agrawal (MIT)

Rethinking pooling in graph neural networks
Diego Mesquita (Aalto University) · Amauri Souza (IFCE) · Samuel Kaski (Aalto University and University of Manchester)

Modeling Shared responses in Neuroimaging Studies through MultiView ICA
Hugo Richard (INRIA) · Luigi Gresele (MPI for Intelligent Systems, Tübingen) · Aapo Hyvarinen (University of Helsinki) · Bertrand Thirion (INRIA) · Alexandre Gramfort (INRIA) · Pierre Ablin (INRIA)

ICE-BeeM: Identifiable Conditional Energy-Based Deep Models Based on Nonlinear ICA
lyes Khemakhem (UCL) · Ricardo Monti (UCL) · Diederik P. Kingma (Google) · Aapo Hyvarinen (University of Helsinki)

Variational Bayesian Monte Carlo with Noisy Likelihoods
Luigi Acerbi (University of Helsinki) 

Towards Scalable Bayesian Learning of Causal DAGs
Jussi Viinikka (University of Helsinki) · Antti Hyttinen (University of Helsinki) · Johan Pensar (University of Oslo) · Mikko Koivisto (University of Helsinki)

Relative gradient optimization of the Jacobian term in unsupervised deep learning
Luigi Gresele (MPI for Intelligent Systems, Tübingen) · Giancarlo Fissore (Inria) · Adrián Javaloy (Saarland University) · Bernhard Schölkopf (MPI for Intelligent Systems) · Aapo Hyvarinen (University of Helsinki)

Dynamic allocation of limited memory resources in reinforcement learning
Nisheet Patel (University of Geneva) · Luigi Acerbi (University of Helsinki) · Alexandre Pouget (University of Geneva)