Giovanni Luca Marchetti

41 papers A* 3A 7Journal 24Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Identifiable Equivariant Networks are Layerwise Equivariant. CoRR Vahid Shahverdi, Giovanni Luca Marchetti, Georg Bökman, Kathlén Kohn
2026	J	`jnl`	Sequential Group Composition: A Window into the Mechanics of Deep Learning. CoRR Giovanni Luca Marchetti, Daniel Kunin, Adele Myers, Francisco Acosta, Nina Miolane
2025	A	`conf`	A Non-Adversarial Approach to Idempotent Generative Modelling. ECAI Mohammed Al-Jaff, Giovanni Luca Marchetti, Michael C. Welle, Jens Lundell, Mats G. Gustafsson, Gustav Eje Henter, Hossein Azizpour, Danica Kragic
2025	J	`jnl`	A Non-Adversarial Approach to Idempotent Generative Modelling. CoRR Mohammed Al-Jaff, Giovanni Luca Marchetti, Michael C. Welle, Jens Lundell, Mats G. Gustafsson, Gustav Eje Henter, Hossein Azizpour, Danica Kragic
2025	J	`jnl`	Alternating Gradient Flows: A Theory of Feature Learning in Two-layer Neural Networks. CoRR Daniel Kunin, Giovanni Luca Marchetti, Feng Chen, Dhruva Karkada, James B. Simon, Michael Robert DeWeese, Surya Ganguli, Nina Miolane
2025	J	`jnl`	An Invitation to Neuroalgebraic Geometry. CoRR Giovanni Luca Marchetti, Vahid Shahverdi, Stefano Mereta, Matthew Trager, Kathlén Kohn
2025	J	`jnl`	Critical Points of Degenerate Metrics on Algebraic Varieties: A Tale of Overparametrization. CoRR Giovanni Luca Marchetti, Erin Connelly, Paul Breiding, Kathlén Kohn
2025	A*	`conf`	Geometry of Lightning Self-Attention: Identifiability and Dimension. ICLR Nathan W. Henry, Giovanni Luca Marchetti, Kathlén Kohn
2025	A	`conf`	HyperSteiner: Computing Heuristic Hyperbolic Steiner Minimal Trees. ALENEX Alejandro García-Castellanos, Aniss Aiman Medbouhi, Giovanni Luca Marchetti, Erik J. Bekkers, Danica Kragic
2025	J	`jnl`	Learning on a Razor's Edge: the Singularity Bias of Polynomial Neural Networks. CoRR Vahid Shahverdi, Giovanni Luca Marchetti, Kathlén Kohn
2025	J	`jnl`	Neural Lattice Reduction: A Self-Supervised Geometric Deep Learning Approach. Trans. Mach. Learn. Res. Giovanni Luca Marchetti, Gabriele Cesa, Kumar Pratik, Arash Behboodi
2025	A	`conf`	On the Geometry and Optimization of Polynomial Convolutional Networks. AISTATS Vahid Shahverdi, Giovanni Luca Marchetti, Kathlén Kohn
2025	—	`conf`	Position: Algebra Unveils Deep Learning - An Invitation to Neuroalgebraic Geometry. ICML (Position Papers) Giovanni Luca Marchetti, Vahid Shahverdi, Stefano Mereta, Matthew Trager, Kathlén Kohn
2025	J	`jnl`	Randomized HyperSteiner: A Stochastic Delaunay Triangulation Heuristic for the Hyperbolic Steiner Minimal Tree. CoRR Aniss Aiman Medbouhi, Alejandro García-Castellanos, Giovanni Luca Marchetti, Daniël M. Pelt, Erik J. Bekkers, Danica Kragic
2025	—	`conf`	Relative Representations: Topological and Geometric Perspectives. UniReps Alejandro García-Castellanos, Giovanni Luca Marchetti, Danica Kragic, Martina Scolamiero
2025	J	`jnl`	Sprecher Networks: A Parameter-Efficient Kolmogorov-Arnold Architecture. CoRR Christian Hägg, Kathlén Kohn, Giovanni Luca Marchetti, Boris Z. Shapiro
2024	J	`jnl`	Geometry of Lightning Self-Attention: Identifiability and Dimension. CoRR Nathan W. Henry, Giovanni Luca Marchetti, Kathlén Kohn
2024	A*	`conf`	Harmonics of Learning: Universal Fourier Features Emerge in Invariant Networks. COLT Giovanni Luca Marchetti, Christopher J. Hillar, Danica Kragic, Sophia Sanborn
2024	J	`jnl`	HyperSteiner: Computing Heuristic Hyperbolic Steiner Minimal Trees. CoRR Alejandro García-Castellanos, Aniss Aiman Medbouhi, Giovanni Luca Marchetti, Erik J. Bekkers, Danica Kragic
2024	—	`conf`	Hyperbolic Delaunay Geometric Alignment. ECML/PKDD (3) Aniss Aiman Medbouhi, Giovanni Luca Marchetti, Vladislav Polianskii, Alexander Kravberg, Petra Poklukar, Anastasia Varava, Danica Kragic
2024	J	`jnl`	Hyperbolic Delaunay Geometric Alignment. CoRR Aniss Aiman Medbouhi, Giovanni Luca Marchetti, Vladislav Polianskii, Alexander Kravberg, Petra Poklukar, Anastasia Varava, Danica Kragic
2024	—	`—`	On Symmetries and Metrics in Geometric Inference. Giovanni Luca Marchetti
2024	J	`jnl`	On the Geometry and Optimization of Polynomial Convolutional Networks. CoRR Vahid Shahverdi, Giovanni Luca Marchetti, Kathlén Kohn
2024	J	`jnl`	Relative Representations: Topological and Geometric Perspectives. CoRR Alejandro García-Castellanos, Giovanni Luca Marchetti, Danica Kragic, Martina Scolamiero
2023	A	`conf`	An Efficient and Continuous Voronoi Density Estimator. AISTATS Giovanni Luca Marchetti, Vladislav Polianskii, Anastasiia Varava, Florian T. Pokorny, Danica Kragic
2023	—	`conf`	Equivariant Representation Learning in the Presence of Stabilizers. ECML/PKDD (4) Luis Armando Pérez Rey, Giovanni Luca Marchetti, Danica Kragic, Dmitri Jarnikov, Mike Holenderski
2023	A	`conf`	Equivariant Representation Learning via Class-Pose Decomposition. AISTATS Giovanni Luca Marchetti, Gustaf Tegnér, Anastasiia Varava, Danica Kragic
2023	J	`jnl`	Equivariant Representations for Non-Free Group Actions. CoRR Luis Armando Pérez Rey, Giovanni Luca Marchetti, Danica Kragic, Dmitri Jarnikov, Mike Holenderski
2023	J	`jnl`	Harmonics of Learning: Universal Fourier Features Emerge in Invariant Networks. CoRR Giovanni Luca Marchetti, Christopher Hillar, Danica Kragic, Sophia Sanborn
2023	—	`conf`	Learning Geometric Representations of Objects via Interaction. ECML/PKDD (4) Alfredo Reichlin, Giovanni Luca Marchetti, Hang Yin, Anastasiia Varava, Danica Kragic
2023	J	`jnl`	Learning Geometric Representations of Objects via Interaction. CoRR Alfredo Reichlin, Giovanni Luca Marchetti, Hang Yin, Anastasiia Varava, Danica Kragic
2023	J	`jnl`	Neural Lattice Reduction: A Self-Supervised Geometric Deep Learning Approach. CoRR Giovanni Luca Marchetti, Gabriele Cesa, Kumar Pratik, Arash Behboodi
2022	A*	`conf`	Active Nearest Neighbor Regression Through Delaunay Refinement. ICML Alexander Kravberg, Giovanni Luca Marchetti, Vladislav Polianskii, Anastasiia Varava, Florian T. Pokorny, Danica Kragic
2022	J	`jnl`	Active Nearest Neighbor Regression Through Delaunay Refinement. CoRR Alexander Kravberg, Giovanni Luca Marchetti, Vladislav Polianskii, Anastasiia Varava, Florian T. Pokorny, Danica Kragic
2022	J	`jnl`	An Efficient and Continuous Voronoi Density Estimator. CoRR Giovanni Luca Marchetti, Vladislav Polianskii, Anastasiia Varava, Florian T. Pokorny, Danica Kragic
2022	A	`conf`	Back to the Manifold: Recovering from Out-of-Distribution States. IROS Alfredo Reichlin, Giovanni Luca Marchetti, Hang Yin, Ali Ghadirzadeh, Danica Kragic
2022	J	`jnl`	Back to the Manifold: Recovering from Out-of-Distribution States. CoRR Alfredo Reichlin, Giovanni Luca Marchetti, Hang Yin, Ali Ghadirzadeh, Danica Kragic
2022	J	`jnl`	Equivariant Representation Learning via Class-Pose Decomposition. CoRR Giovanni Luca Marchetti, Gustaf Tegnér, Anastasiia Varava, Danica Kragic
2022	J	`jnl`	Voronoi Density Estimator for High-Dimensional Data: Computation, Compactification and Convergence. CoRR Vladislav Polianskii, Giovanni Luca Marchetti, Alexander Kravberg, Anastasiia Varava, Florian T. Pokorny, Danica Kragic
2022	A	`conf`	Voronoi density estimator for high-dimensional data: Computation, compactification and convergence. UAI Vladislav Polianskii, Giovanni Luca Marchetti, Alexander Kravberg, Anastasiia Varava, Florian T. Pokorny, Danica Kragic
2021	—	`conf`	Learning Coarsened Dynamic Graph Representations for Deformable Object Manipulation. ICAR Giovanni Luca Marchetti, Marco Moletta, Gustaf Tegnér, Peiyang Shi, Anastasiia Varava, Alexander Kravchenko, Danica Kragic