Luca Ambrogioni

66 papers A* 10A 5Journal 47Unranked 4

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Categorical Flow Maps. CoRR Daan Roos, Oscar Davis, Floor Eijkelboom, Michael M. Bronstein, Max Welling, Ismail Ilkan Ceylan, Luca Ambrogioni, Jan-Willem van de Meent
2026	J	`jnl`	Emergence of Distortions in High-Dimensional Guided Diffusion Models. CoRR Enrico Ventura, Beatrice Achilli, Luca Ambrogioni, Carlo Lucibello
2026	J	`jnl`	How Out-of-Equilibrium Phase Transitions can Seed Pattern Formation in Trained Diffusion Models. CoRR Luca Ambrogioni
2026	J	`jnl`	Improved Sampling Schedules for Discrete Diffusion Models. CoRR Alberto Foresti, Mustapha Bounoua, Giulio Franzese, Luca Ambrogioni, Pietro Michiardi
2026	J	`jnl`	Information-Guided Noise Allocation for Efficient Diffusion Training. CoRR Gabriel Raya, Bac Nguyen, Georgios Batzolis, Yuhta Takida, Dejan Stancevic, Naoki Murata, Chieh-Hsin Lai, Yuki Mitsufuji, Luca Ambrogioni
2026	J	`jnl`	The Entropic Signature of Class Speciation in Diffusion Models. CoRR Florian Handke, Dejan Stancevic, Felix Koulischer, Thomas Demeester, Luca Ambrogioni
2026	J	`jnl`	The Information Dynamics of Generative Diffusion. Entropy Dejan Stancevic, Luca Ambrogioni
2025	J	`jnl`	CoVAE: Consistency Training of Variational Autoencoders. CoRR Gianluigi Silvestri, Luca Ambrogioni
2025	A*	`conf`	Dynamic Negative Guidance of Diffusion Models. ICLR Felix Koulischer, Johannes Deleu, Gabriel Raya, Thomas Demeester, Luca Ambrogioni
2025	J	`jnl`	Entropic Time Schedulers for Generative Diffusion Models. CoRR Dejan Stancevic, Luca Ambrogioni
2025	J	`jnl`	Feedback Guidance of Diffusion Models. CoRR Felix Koulischer, Florian Handke, Johannes Deleu, Thomas Demeester, Luca Ambrogioni
2025	A*	`conf`	Manifolds, Random Matrices and Spectral Gaps: The geometric phases of generative diffusion. ICLR Enrico Ventura, Beatrice Achilli, Gianluigi Silvestri, Carlo Lucibello, Luca Ambrogioni
2025	J	`jnl`	Measuring Semantic Information Production in Generative Diffusion Models. CoRR Florian Handke, Felix Koulischer, Gabriel Raya, Luca Ambrogioni
2025	J	`jnl`	Memorization to Generalization: Emergence of Diffusion Models from Associative Memory. CoRR Bao Pham, Gabriel Raya, Matteo Negri, Mohammed J. Zaki, Luca Ambrogioni, Dmitry Krotov
2025	J	`jnl`	The Information Dynamics of Generative Diffusion. CoRR Luca Ambrogioni
2025	J	`jnl`	The Statistical Thermodynamics of Generative Diffusion Models: Phase Transitions, Symmetry Breaking, and Critical Instability. Entropy Luca Ambrogioni
2025	J	`jnl`	Training Consistency Models with Variational Noise Coupling. CoRR Gianluigi Silvestri, Luca Ambrogioni, Chieh-Hsin Lai, Yuhta Takida, Yuki Mitsufuji
2025	A*	`conf`	VCT: Training Consistency Models with Variational Noise Coupling. ICML Gianluigi Silvestri, Luca Ambrogioni, Chieh-Hsin Lai, Yuhta Takida, Yuki Mitsufuji
2024	J	`jnl`	Dynamic Negative Guidance of Diffusion Models. CoRR Felix Koulischer, Johannes Deleu, Gabriel Raya, Thomas Demeester, Luca Ambrogioni
2024	J	`jnl`	In Search of Dispersed Memories: Generative Diffusion Models Are Associative Memory Networks. Entropy Luca Ambrogioni
2024	J	`jnl`	Losing dimensions: Geometric memorization in generative diffusion. CoRR Beatrice Achilli, Enrico Ventura, Gianluigi Silvestri, Bao Pham, Gabriel Raya, Dmitry Krotov, Carlo Lucibello, Luca Ambrogioni
2024	J	`jnl`	Manifolds, Random Matrices and Spectral Gaps: The geometric phases of generative diffusion. CoRR Enrico Ventura, Beatrice Achilli, Gianluigi Silvestri, Carlo Lucibello, Luca Ambrogioni
2024	J	`jnl`	Robust and highly scalable estimation of directional couplings from time-shifted signals. CoRR Luca Ambrogioni, Louis Rouillard, Demian Wassermann
2024	A*	`conf`	Stationarity without mean reversion in improper Gaussian processes. ICML Luca Ambrogioni
2023	A*	`conf`	Deterministic training of generative autoencoders using invertible layers. ICLR Gianluigi Silvestri, Daan Roos, Luca Ambrogioni
2023	J	`jnl`	Gradient-adjusted Incremental Target Propagation Provides Effective Credit Assignment in Deep Neural Networks. Trans. Mach. Learn. Res. Sander Dalm, Nasir Ahmad, Luca Ambrogioni, Marcel van Gerven
2023	J	`jnl`	In search of dispersed memories: Generative diffusion models are associative memory networks. CoRR Luca Ambrogioni
2023	A*	`conf`	Spontaneous symmetry breaking in generative diffusion models. NeurIPS Gabriel Raya, Luca Ambrogioni
2023	J	`jnl`	Spontaneous symmetry breaking in generative diffusion models. CoRR Gabriel Raya, Luca Ambrogioni
2023	J	`jnl`	Stationarity without mean reversion: Improper Gaussian process regression and improper kernels. CoRR Luca Ambrogioni
2023	J	`jnl`	The statistical thermodynamics of generative diffusion models. CoRR Luca Ambrogioni
2022	J	`jnl`	Closing the gap: Exact maximum likelihood training of generative autoencoders using invertible layers. CoRR Gianluigi Silvestri, Daan Roos, Luca Ambrogioni
2022	A*	`conf`	Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modeling. ICLR Gianluigi Silvestri, Emily Fertig, Dave Moore, Luca Ambrogioni
2022	—	`conf`	Towards Naturalistic Speech Decoding from Intracranial Brain Data. EMBC Julia Berezutskaya, Luca Ambrogioni, Nick F. Ramsey, Marcel A. J. van Gerven
2021	A	`conf`	Automatic structured variational inference. AISTATS Luca Ambrogioni, Kate Lin, Emily Fertig, Sharad Vikram, Max Hinne, Dave Moore, Marcel van Gerven
2021	A*	`conf`	Automatic variational inference with cascading flows. ICML Luca Ambrogioni, Gianluigi Silvestri, Marcel van Gerven
2021	J	`jnl`	Automatic variational inference with cascading flows. CoRR Luca Ambrogioni, Gianluigi Silvestri, Marcel van Gerven
2021	J	`jnl`	Embedded-model flows: Combining the inductive biases of model-free deep learning and explicit probabilistic modeling. CoRR Gianluigi Silvestri, Emily Fertig, Dave Moore, Luca Ambrogioni
2021	J	`jnl`	End-to-end neural system identification with neural information flow. PLoS Comput. Biol. Katja Seeliger, Luca Ambrogioni, Yagmur Güçlütürk, L. M. van den Bulk, Umut Güçlü, Marcel A. J. van Gerven
2021	J	`jnl`	Knowledge is reward: Learning optimal exploration by predictive reward cashing. CoRR Luca Ambrogioni
2021	J	`jnl`	Scaling up learning with GAIT-prop. CoRR Sander Dalm, Nasir Ahmad, Luca Ambrogioni, Marcel van Gerven
2020	J	`jnl`	Automatic structured variational inference. CoRR Luca Ambrogioni, Max Hinne, Marcel van Gerven
2020	J	`jnl`	Explainable 3D Convolutional Neural Networks by Learning Temporal Transformations. CoRR Gabriëlle Ras, Luca Ambrogioni, Pim Haselager, Marcel A. J. van Gerven, Umut Güçlü
2020	A*	`conf`	GAIT-prop: A biologically plausible learning rule derived from backpropagation of error. NeurIPS Nasir Ahmad, Marcel A. J. van Gerven, Luca Ambrogioni
2020	J	`jnl`	GAIT-prop: A biologically plausible learning rule derived from backpropagation of error. CoRR Nasir Ahmad, Marcel A. J. van Gerven, Luca Ambrogioni
2020	J	`jnl`	Spike-Timing-Dependent Inference of Synaptic Weights. CoRR Nasir Ahmad, Luca Ambrogioni, Marcel A. J. van Gerven
2020	A	`conf`	The Indian Chefs Process. UAI Patrick Dallaire, Luca Ambrogioni, Ludovic Trottier, Umut Güçlü, Max Hinne, Philippe Giguère, Marcel van Gerven, François Laviolette
2020	J	`jnl`	The Indian Chefs Process. CoRR Patrick Dallaire, Luca Ambrogioni, Ludovic Trottier, Umut Güçlü, Max Hinne, Philippe Giguère, Brahim Chaib-draa, Marcel van Gerven, François Laviolette
2019	J	`jnl`	Background Hardly Matters: Understanding Personality Attribution in Deep Residual Networks. CoRR Gabriëlle Ras, Ron Dotsch, Luca Ambrogioni, Umut Güçlü, Marcel A. J. van Gerven
2019	J	`jnl`	Causal inference using Bayesian non-parametric quasi-experimental design. CoRR Max Hinne, Marcel A. J. van Gerven, Luca Ambrogioni
2019	J	`jnl`	Complex-valued gaussian process regression for time series analysis. Signal Process. Luca Ambrogioni, Eric Maris
2019	A	`conf`	Forward Amortized Inference for Likelihood-Free Variational Marginalization. AISTATS Luca Ambrogioni, Umut Güçlü, Julia Berezutskaya, Eva W. P. van den Borne, Yagmur Güçlütürk, Max Hinne, Eric Maris, Marcel van Gerven
2019	—	`conf`	Segmentation of Photovoltaic Panels in Aerial Photography Using Group Equivariant FCNs. BNAIC/BENELEARN Lars Bokkers, Luca Ambrogioni, Umut Güçlü
2019	A	`conf`	SpikeCaKe: Semi-Analytic Nonparametric Bayesian Inference for Spike-Spike Neuronal Connectivity. AISTATS Luca Ambrogioni, Patrick Ebel, Max Hinne, Umut Güçlü, Marcel van Gerven, Eric Maris
2019	—	`conf`	Temporal Factorization of 3D Convolutional Kernels. BNAIC/BENELEARN Gabrielle Ras, Luca Ambrogioni, Umut Güçlü, Marcel van Gerven
2019	J	`jnl`	Temporal Factorization of 3D Convolutional Kernels. CoRR Gabriëlle Ras, Luca Ambrogioni, Umut Güçlü, Marcel A. J. van Gerven
2019	J	`jnl`	k-GANs: Ensemble of Generative Models with Semi-Discrete Optimal Transport. CoRR Luca Ambrogioni, Umut Güçlü, Marcel van Gerven
2018	J	`jnl`	Forward Amortized Inference for Likelihood-Free Variational Marginalization. CoRR Luca Ambrogioni, Umut Güçlü, Julia Berezutskaya, Eva W. P. van den Borne, Yagmur Güçlütürk, Max Hinne, Eric Maris, Marcel A. J. van Gerven
2018	J	`jnl`	Generative adversarial networks for reconstructing natural images from brain activity. NeuroImage Katja Seeliger, Umut Güçlü, Luca Ambrogioni, Yagmur Güçlütürk, Marcel A. J. van Gerven
2018	A	`conf`	Integral Transforms from Finite Data: An Application of Gaussian Process Regression to Fourier Analysis. AISTATS Luca Ambrogioni, Eric Maris
2018	J	`jnl`	Wasserstein Variational Gradient Descent: From Semi-Discrete Optimal Transport to Ensemble Variational Inference. CoRR Luca Ambrogioni, Umut Güçlü, Yagmur Güçlütürk, Marcel van Gerven
2018	A*	`conf`	Wasserstein Variational Inference. NeurIPS Luca Ambrogioni, Umut Güçlü, Yagmur Güçlütürk, Max Hinne, Marcel A. J. van Gerven, Eric Maris
2018	J	`jnl`	Wasserstein Variational Inference. CoRR Luca Ambrogioni, Umut Güçlü, Yagmur Güçlütürk, Max Hinne, Marcel A. J. van Gerven, Eric Maris
2017	J	`jnl`	Dynamic decomposition of spatiotemporal neural signals. PLoS Comput. Biol. Luca Ambrogioni, Marcel A. J. van Gerven, Eric Maris
2017	—	`conf`	GP CaKe: Effective brain connectivity with causal kernels. NIPS Luca Ambrogioni, Max Hinne, Marcel van Gerven, Eric Maris
2014	J	`jnl`	Structurally-informed Bayesian functional connectivity analysis. NeuroImage Max Hinne, Luca Ambrogioni, Ronald J. Janssen, Tom Heskes, Marcel A. J. van Gerven