Luca Ambrogioni

According to our database, Luca Ambrogioni authored at least 40 papers between 2014 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of three.

2024

In Search of Dispersed Memories: Generative Diffusion Models Are Associative Memory Networks.

Luca Ambrogioni

Entropy, May, 2024

Dynamic Negative Guidance of Diffusion Models.

Felix Koulischer, Johannes Deleu, Gabriel Raya, Thomas Demeester, Luca Ambrogioni

CoRR, 2024

Losing dimensions: Geometric memorization in generative diffusion.

Beatrice Achilli, Enrico Ventura, Gianluigi Silvestri, Bao Pham, Gabriel Raya, Dmitry Krotov, Carlo Lucibello, Luca Ambrogioni

CoRR, 2024

Manifolds, Random Matrices and Spectral Gaps: The geometric phases of generative diffusion.

Enrico Ventura, Beatrice Achilli, Gianluigi Silvestri, Carlo Lucibello, Luca Ambrogioni

CoRR, 2024

Robust and highly scalable estimation of directional couplings from time-shifted signals.

Luca Ambrogioni, Louis Rouillard, Demian Wassermann

CoRR, 2024

Stationarity without mean reversion in improper Gaussian processes.

Luca Ambrogioni

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Gradient-adjusted Incremental Target Propagation Provides Effective Credit Assignment in Deep Neural Networks.

Sander Dalm, Nasir Ahmad, Luca Ambrogioni, Marcel van Gerven

Trans. Mach. Learn. Res., 2023

The statistical thermodynamics of generative diffusion models.

Luca Ambrogioni

CoRR, 2023

Stationarity without mean reversion: Improper Gaussian process regression and improper kernels.

Luca Ambrogioni

CoRR, 2023

Spontaneous symmetry breaking in generative diffusion models.

Gabriel Raya, Luca Ambrogioni

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Deterministic training of generative autoencoders using invertible layers.

Gianluigi Silvestri, Daan Roos, Luca Ambrogioni

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Closing the gap: Exact maximum likelihood training of generative autoencoders using invertible layers.

Gianluigi Silvestri, Daan Roos, Luca Ambrogioni

CoRR, 2022

Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modeling.

Gianluigi Silvestri, Emily Fertig, Dave Moore, Luca Ambrogioni

Proceedings of the Tenth International Conference on Learning Representations, 2022

Towards Naturalistic Speech Decoding from Intracranial Brain Data.

Julia Berezutskaya, Luca Ambrogioni, Nick F. Ramsey, Marcel A. J. van Gerven

Proceedings of the 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2022

2021

End-to-end neural system identification with neural information flow.

Katja Seeliger, Luca Ambrogioni, Yagmur Güçlütürk, L. M. van den Bulk, Umut Güçlü, Marcel A. J. van Gerven

PLoS Comput. Biol., 2021

Knowledge is reward: Learning optimal exploration by predictive reward cashing.

Luca Ambrogioni

CoRR, 2021

Scaling up learning with GAIT-prop.

Sander Dalm, Nasir Ahmad, Luca Ambrogioni, Marcel van Gerven

CoRR, 2021

Automatic variational inference with cascading flows.

Luca Ambrogioni, Gianluigi Silvestri, Marcel van Gerven

Proceedings of the 38th International Conference on Machine Learning, 2021

Automatic structured variational inference.

Luca Ambrogioni, Kate Lin, Emily Fertig, Sharad Vikram, Max Hinne, Dave Moore, Marcel van Gerven

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

Explainable 3D Convolutional Neural Networks by Learning Temporal Transformations.

Gabriëlle Ras, Luca Ambrogioni, Pim Haselager, Marcel A. J. van Gerven, Umut Güçlü

CoRR, 2020

Spike-Timing-Dependent Inference of Synaptic Weights.

Nasir Ahmad, Luca Ambrogioni, Marcel A. J. van Gerven

CoRR, 2020

Automatic structured variational inference.

Luca Ambrogioni, Max Hinne, Marcel van Gerven

CoRR, 2020

The Indian Chefs Process.

Patrick Dallaire, Luca Ambrogioni, Ludovic Trottier, Umut Güçlü, Max Hinne, Philippe Giguère, Brahim Chaib-draa, Marcel van Gerven, François Laviolette

CoRR, 2020

The Indian Chefs Process.

Patrick Dallaire, Luca Ambrogioni, Ludovic Trottier, Umut Güçlü, Max Hinne, Philippe Giguère, Marcel van Gerven, François Laviolette

Proceedings of the Thirty-Sixth Conference on Uncertainty in Artificial Intelligence, 2020

GAIT-prop: A biologically plausible learning rule derived from backpropagation of error.

Nasir Ahmad, Marcel A. J. van Gerven, Luca Ambrogioni

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

Complex-valued gaussian process regression for time series analysis.

Luca Ambrogioni, Eric Maris

Signal Process., 2019

Background Hardly Matters: Understanding Personality Attribution in Deep Residual Networks.

Gabriëlle Ras, Ron Dotsch, Luca Ambrogioni, Umut Güçlü, Marcel A. J. van Gerven

CoRR, 2019

Causal inference using Bayesian non-parametric quasi-experimental design.

Max Hinne, Marcel A. J. van Gerven, Luca Ambrogioni

CoRR, 2019

k-GANs: Ensemble of Generative Models with Semi-Discrete Optimal Transport.

Luca Ambrogioni, Umut Güçlü, Marcel van Gerven

CoRR, 2019

Temporal Factorization of 3D Convolutional Kernels.

Gabrielle Ras, Luca Ambrogioni, Umut Güçlü, Marcel van Gerven

Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

Segmentation of Photovoltaic Panels in Aerial Photography Using Group Equivariant FCNs.

Lars Bokkers, Luca Ambrogioni, Umut Güçlü

Proceedings of the 31st Benelux Conference on Artificial Intelligence (BNAIC 2019) and the 28th Belgian Dutch Conference on Machine Learning (Benelearn 2019), 2019

Forward Amortized Inference for Likelihood-Free Variational Marginalization.

Luca Ambrogioni, Umut Güçlü, Julia Berezutskaya, Eva W. P. van den Borne, Yagmur Güçlütürk, Max Hinne, Eric Maris, Marcel van Gerven

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

SpikeCaKe: Semi-Analytic Nonparametric Bayesian Inference for Spike-Spike Neuronal Connectivity.

Luca Ambrogioni, Patrick Ebel, Max Hinne, Umut Güçlü, Marcel van Gerven, Eric Maris

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Generative adversarial networks for reconstructing natural images from brain activity.

Katja Seeliger, Umut Güçlü, Luca Ambrogioni, Yagmur Güçlütürk, Marcel A. J. van Gerven

NeuroImage, 2018

Wasserstein Variational Gradient Descent: From Semi-Discrete Optimal Transport to Ensemble Variational Inference.

Luca Ambrogioni, Umut Güçlü, Yagmur Güçlütürk, Marcel van Gerven

CoRR, 2018

Wasserstein Variational Inference.

Luca Ambrogioni, Umut Güçlü, Yagmur Güçlütürk, Max Hinne, Marcel A. J. van Gerven, Eric Maris

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

Integral Transforms from Finite Data: An Application of Gaussian Process Regression to Fourier Analysis.

Luca Ambrogioni, Eric Maris

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018

2017

Dynamic decomposition of spatiotemporal neural signals.

Luca Ambrogioni, Marcel A. J. van Gerven, Eric Maris

PLoS Comput. Biol., 2017

GP CaKe: Effective brain connectivity with causal kernels.

Luca Ambrogioni, Max Hinne, Marcel van Gerven, Eric Maris

Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2014

Structurally-informed Bayesian functional connectivity analysis.

Max Hinne, Luca Ambrogioni, Ronald J. Janssen, Tom Heskes, Marcel A. J. van Gerven

NeuroImage, 2014