Arno Solin
46 papers · 2014–2025 · 11 conferences · across top CS/AI conferences
Achievements
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๐ Conference Polyglot (11) ๐ฃ Hot Topic Early Bird ๐ Interdisciplinary Bridge ๐งญ Keyword Pioneer ๐ Academic Marathon (11)
๐ฃ
Hot Topic Early Bird
๐
Cross-Pollinator
(15)
๐บ๏ธ
Taxonomy Completionist
(44)
๐ค
Dynamic Duo
(11)
๐
Grand Slam
๐ฌ
Deep Specialist
(20)
๐
Keyword Champion
(2)
๐
Conference Pioneer
๐๏ธ
Keyword Collector
(124)
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Prolific Year
(8)
๐ฅ
Unstoppable
(8)
๐
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
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 FokkerโPlanckโKolmogorov 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