Arno Solin

Cross-View Splatter: Feed-Forward View Synthesis with Georeferenced Images CVPR 2026 Approximate Bayesian Inference via Bitstring Representations UAI 2025 DeSplat: Decomposed Gaussian Splatting for Distractor-Free Rendering CVPR 2025 Discrete Codebook World Models for Continuous Control ICLR 2025 Equivariant Denoisers Cannot Copy Graphs: Align Your Graph Diffusion Models ICLR 2025 Flatness Improves Backbone Generalisation in Few-Shot Classification WACV 2025 Free Hunch: Denoiser Covariance Estimation for Diffusion Models Without Extra Costs ICLR 2025 Progressive Tempering Sampler with Diffusion ICML 2025 Streamlining Prediction in Bayesian Deep Learning ICLR 2025 Fixing Overconfidence in Dynamic Neural Networks WACV 2024 Function-space Parameterization of Neural Networks for Sequential Learning ICLR 2024 Gaussian Splatting on the Move: Blur and Rolling Shutter Compensation for Natural Camera Motion ECCV 2024 Physics-Informed Variational State-Space Gaussian Processes NeurIPS 2024 Subtractive Mixture Models via Squaring: Representation and Learning ICLR 2024 Variational Gaussian Process Diffusion Processes AISTATS 2024 Bayes-Newton Methods for Approximate Bayesian Inference with PSD Guarantees JMLR 2023 Expansion of Visual Hints for Improved Generalization in Stereo Matching WACV 2023 Generative Modelling with Inverse Heat Dissipation ICLR 2023 Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models ICML 2023 Memory-Based Dual Gaussian Processes for Sequential Learning ICML 2023 MixupE: Understanding and improving Mixup from directional derivative perspective UAI 2023 HybVIO: Pushing the Limits of Real-Time Visual-Inertial Odometry WACV 2022 Non-separable Spatio-temporal Graph Kernels via SPDEs AISTATS 2022 Uncertainty-Guided Source-Free Domain Adaptation ECCV 2022 Combining pseudo-point and state space approximations for sum-separable Gaussian Processes UAI 2021 Dual Parameterization of Sparse Variational Gaussian Processes NeurIPS 2021 Gaussian Process Priors for View-Aware Inference AAAI 2021 Novel View Synthesis via Depth-Guided Skip Connections WACV 2021 Periodic Activation Functions Induce Stationarity NeurIPS 2021 Scalable Inference in SDEs by Direct Matching of the Fokker–Planck–Kolmogorov Equation NeurIPS 2021 Sparse Algorithms for Markovian Gaussian Processes AISTATS 2021 Spatio-Temporal Variational Gaussian Processes NeurIPS 2021 Deep Automodulators NeurIPS 2020 Scalable Exact Inference in Multi-Output Gaussian Processes ICML 2020 State Space Expectation Propagation: Efficient Inference Schemes for Temporal Gaussian Processes ICML 2020 Stationary Activations for Uncertainty Calibration in Deep Learning NeurIPS 2020 Towards Photographic Image Manipulation with Balanced Growing of Generative Autoencoders WACV 2020 End-to-End Probabilistic Inference for Nonstationary Audio Analysis ICML 2019 Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features AISTATS 2019 Multi-View Stereo by Temporal Nonparametric Fusion ICCV 2019 ADVIO: An Authentic Dataset for Visual-Inertial Odometry ECCV 2018 Infinite-Horizon Gaussian Processes NeurIPS 2018 State Space Gaussian Processes with Non-Gaussian Likelihood ICML 2018 Variational Fourier Features for Gaussian Processes JMLR 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