← Authors

Arno Solin

46 papers · 2014–2025 · 11 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (11) πŸƒ Academic Marathon (11) 🌈 Renaissance Researcher (6) πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (15) πŸ—ΊοΈ Taxonomy Completionist (44) 🀝 Dynamic Duo (11) πŸ† Grand Slam πŸ”¬ Deep Specialist (20) πŸ† Keyword Champion (2) πŸš€ Conference Pioneer πŸ—ƒοΈ Keyword Collector (124) ⚑ Prolific Year (8) πŸ”₯ Unstoppable (8) πŸ’Ž Century Club (46)

Conferences

NIPS (8) AISTATS (7) ICLR (7) ICML (7) WACV (6) ECCV (3) UAI (3) JMLR (2) AAAI (1) CVPR (1) ICCV (1)

Top co-authors

Juho Kannala (11) Martin Trapp (7) Yuxin Hou (5) Simo SΓ€rkkΓ€ (4) William Wilkinson (4) Markus Heinonen (4) Severi Rissanen (4) Prakhar Verma (3) Esa Rahtu (3) Vincent ADAM (3)

Keywords

gaussian process (19) variational inference (13) state space model (7) expectation propagation (7) bayesian inference (5) kalman filter (3) natural gradient (3) generative model (2) pose estimation (2) sparse approximation (2) time series (2) image generation (2) uncertainty quantification (2) gaussian processes (2) hyperparameter learning (2) spatio-temporal modeling (2) depth estimation (2) laplace approximation (2) kalman filtering (2) state-space model (2)

Papers

Progressive Tempering Sampler with Diffusion ICML 2025
Flatness Improves Backbone Generalisation in Few-Shot Classification WACV 2025
Equivariant Denoisers Cannot Copy Graphs: Align Your Graph Diffusion Models ICLR 2025
Streamlining Prediction in Bayesian Deep Learning ICLR 2025
Discrete Codebook World Models for Continuous Control ICLR 2025
Approximate Bayesian Inference via Bitstring Representations UAI 2025
DeSplat: Decomposed Gaussian Splatting for Distractor-Free Rendering CVPR 2025
Free Hunch: Denoiser Covariance Estimation for Diffusion Models Without Extra Costs ICLR 2025
Function-space Parameterization of Neural Networks for Sequential Learning ICLR 2024
Physics-Informed Variational State-Space Gaussian Processes NIPS 2024
Fixing Overconfidence in Dynamic Neural Networks WACV 2024
Variational Gaussian Process Diffusion Processes AISTATS 2024
Gaussian Splatting on the Move: Blur and Rolling Shutter Compensation for Natural Camera Motion ECCV 2024
Subtractive Mixture Models via Squaring: Representation and Learning ICLR 2024
Expansion of Visual Hints for Improved Generalization in Stereo Matching WACV 2023
Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models ICML 2023
Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees JMLR 2023
Memory-Based Dual Gaussian Processes for Sequential Learning ICML 2023
MixupE: Understanding and improving Mixup from directional derivative perspective UAI 2023
Generative Modelling with Inverse Heat Dissipation ICLR 2023
Uncertainty-Guided Source-Free Domain Adaptation ECCV 2022
Non-separable Spatio-temporal Graph Kernels via SPDEs AISTATS 2022
HybVIO: Pushing the Limits of Real-Time Visual-Inertial Odometry WACV 2022
Scalable Inference in SDEs by Direct Matching of the Fokker–Planck–Kolmogorov Equation NIPS 2021
Dual Parameterization of Sparse Variational Gaussian Processes NIPS 2021
Spatio-Temporal Variational Gaussian Processes NIPS 2021
Gaussian Process Priors for View-Aware Inference AAAI 2021
Sparse Algorithms for Markovian Gaussian Processes AISTATS 2021
Novel View Synthesis via Depth-Guided Skip Connections WACV 2021
Combining pseudo-point and state space approximations for sum-separable Gaussian Processes UAI 2021
Periodic Activation Functions Induce Stationarity NIPS 2021
Towards Photographic Image Manipulation with Balanced Growing of Generative Autoencoders WACV 2020
Stationary Activations for Uncertainty Calibration in Deep Learning NIPS 2020
Deep Automodulators NIPS 2020
Scalable Exact Inference in Multi-Output Gaussian Processes ICML 2020
State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian Processes ICML 2020
End-to-End Probabilistic Inference for Nonstationary Audio Analysis ICML 2019
Multi-View Stereo by Temporal Nonparametric Fusion ICCV 2019
Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features AISTATS 2019
ADVIO: An Authentic Dataset for Visual-Inertial Odometry ECCV 2018
Variational Fourier Features for Gaussian Processes JMLR 2018
State Space Gaussian Processes with Non-Gaussian Likelihood ICML 2018
Infinite-Horizon Gaussian Processes NIPS 2018
Computationally Efficient Bayesian Learning of Gaussian Process State Space Models AISTATS 2016
State Space Methods for Efficient Inference in Student-t Process Regression AISTATS 2015
Explicit Link Between Periodic Covariance Functions and State Space Models AISTATS 2014