Guido Mont\'ufar
Identifiers
- name variant Guido Mont\'ufar 0.60 · backfill
Papers (47)
- TriSearch: Learning to Optimize Triangulations via Bistellar Flips cs.LG · 2026 · author #2
- The Symmetries of Three-Layer ReLU Networks cs.LG · 2026 · author #3
- Stress-Testing Neural Network Verifiers with Provably Robust Instances cs.LG · 2026 · author #5
- Differentiable Optimization Layers for Guaranteed Fairness in Deep Learning cs.LG · 2026 · author #3
- Most ReLU Networks Admit Identifiable Parameters cs.LG · 2026 · author #2
- Algebraic Invariants of Lightning Self-Attention math.AG · 2026 · author #3
- Robustness Verification of Polynomial Neural Networks stat.ML · 2026 · author #3
- Understanding Learning Invariance in Deep Linear Networks stat.ML · 2025 · author #2
- Demystifying Topological Message-Passing with Relational Structures: A Case Study on Oversquashing in Simplicial Message-Passing cs.LG · 2025 · author #5
- Implicit Bias of Mirror Flow for Shallow Neural Networks in Univariate Regression stat.ML · 2024 · author #2
- Bounds for the smallest eigenvalue of the NTK for arbitrary spherical data of arbitrary dimension stat.ML · 2024 · author #3
- Fisher-Rao Gradient Flows of Linear Programs and State-Action Natural Policy Gradients math.OC · 2024 · author #3
- The Real Tropical Geometry of Neural Networks math.CO · 2024 · author #3
- Benign overfitting in leaky ReLU networks with moderate input dimension cs.LG · 2024 · author #4
- Pull-back Geometry of Persistent Homology Encodings math.AT · 2023 · author #5
- Mildly Overparameterized ReLU Networks Have a Favorable Loss Landscape cs.LG · 2023 · author #4
- Function Space and Critical Points of Linear Convolutional Networks cs.LG · 2023 · author #2
- Critical Points and Convergence Analysis of Generative Deep Linear Networks Trained with Bures-Wasserstein Loss stat.ML · 2023 · author #4
- Expected Gradients of Maxout Networks and Consequences to Parameter Initialization stat.ML · 2023 · author #2
- Algebraic optimization of sequential decision problems math.OC · 2022 · author #3
- Geometry and convergence of natural policy gradient methods math.OC · 2022 · author #2
- FoSR: First-order spectral rewiring for addressing oversquashing in GNNs cs.LG · 2022 · author #3
- Enumeration of max-pooling responses with generalized permutohedra math.CO · 2022 · author #5
- Oversquashing in GNNs through the lens of information contraction and graph expansion cs.LG · 2022 · author #5
- On the effectiveness of persistent homology math.AT · 2022 · author #2
- Solving infinite-horizon POMDPs with memoryless stochastic policies in state-action space cs.LG · 2022 · author #2
- Continuity and Additivity Properties of Information Decompositions cs.IT · 2022 · author #4
- Training Wasserstein GANs without gradient penalties cs.LG · 2021 · author #3
- Learning curves for Gaussian process regression with power-law priors and targets cs.LG · 2021 · author #3
- The Geometry of Memoryless Stochastic Policy Optimization in Infinite-Horizon POMDPs math.OC · 2021 · author #2
- Geometry of Linear Convolutional Networks cs.LG · 2021 · author #3
- On the Expected Complexity of Maxout Networks stat.ML · 2021 · author #2
- Weisfeiler and Lehman Go Cellular: CW Networks cs.LG · 2021 · author #6
- Information Complexity and Generalization Bounds cs.LG · 2021 · author #2
- Sharp bounds for the number of regions of maxout networks and vertices of Minkowski sums math.CO · 2021 · author #1
- Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks cs.LG · 2021 · author #5
- Can neural networks learn persistent homology features? cs.LG · 2020 · author #1
- Distributed Learning via Filtered Hyperinterpolation on Manifolds math.NA · 2020 · author #1
- Implicit Bias of Gradient Descent for Mean Squared Error Regression with Two-Layer Wide Neural Networks stat.ML · 2020 · author #2
- Optimization Theory for ReLU Neural Networks Trained with Normalization Layers cs.LG · 2020 · author #3
- Wasserstein Distance to Independence Models math.OC · 2020 · author #3
- Stochastic Feedforward Neural Networks: Universal Approximation cs.LG · 2019 · author #2
- How Well Do WGANs Estimate the Wasserstein Metric? cs.LG · 2019 · author #2
- Factorized Mutual Information Maximization cs.IT · 2019 · author #2
- The Variational Deficiency Bottleneck cs.IT · 2018 · author #2
- Computing the Unique Information cs.IT · 2017 · author #3
- On the Number of Linear Regions of Deep Neural Networks stat.ML · 2014 · author #1
Mentions
- 2506.13714 #2 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2506.06582 #5 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2410.03988 #2 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2403.19448 #3 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2403.06903 #4 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2405.14630 #3 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2403.11871 #3 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2310.07073 #5 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2211.02105 #2 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2305.19510 #4 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2304.05752 #2 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2209.14978 #5 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2303.03027 #4 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2204.10982 #4 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2006.07356 #2 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2301.06956 #2 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2210.11790 #3 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2206.10551 #2 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2211.09439 #3 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2104.08135 #1 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2208.03471 #5 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2108.01538 #3 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2205.14098 #2 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2110.07409 #2 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2106.12575 #6 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2107.00379 #2 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2110.12231 #3 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2110.14150 #3 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2105.01747 #2 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2103.03212 #5 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2011.14688 #1 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 1810.11677 #2 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2003.06725 #3 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2007.09392 #1 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2006.06878 #3 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 1910.09763 #2 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 1910.03875 #2 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 1906.05460 #2 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 1709.07487 #3 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 1402.1869 #1 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 1402.1869 #1 · backfill · confidence 0.70 Guido Mont\'ufar
- 2605.30220 #2 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2605.03601 #2 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2605.18319 #3 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2605.17153 #5 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
- 2605.17118 #3 · arxiv_oai · confidence 0.70 Guido Mont\'ufar
Frequent Coauthors
- Pradeep Kr. Banerjee 7 shared papers
- Johannes M\"uller 5 shared papers
- Kedar Karhadkar 5 shared papers
- Nina Otter 5 shared papers
- Yu Guang Wang 4 shared papers
- Hanna Tseran 3 shared papers
- Hao Duan 3 shared papers
- Michael Murray 3 shared papers
- Thomas Merkh 3 shared papers
- Yulia Alexandr 3 shared papers
- Cristian Bodnar 2 shared papers
- David Troxell 2 shared papers
- Fabrizio Frasca 2 shared papers
- Hui Jin 2 shared papers
- Johannes Rauh 2 shared papers
- Kathl\'en Kohn 2 shared papers
- Matthew Trager 2 shared papers
- Michael Bronstein 2 shared papers
- Moritz Grillo 2 shared papers
- Pietro Li\`o 2 shared papers