Guido Montúfar

ORCID

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 95

Top Venues

CoRR

ICML

ICLR

SIAM J. Appl. Algebra Geom.

Publications

Kedar Karhadkar, Michael Murray, Hanna Tseran, Guido Montúfar
Mildly Overparameterized ReLU Networks Have a Favorable Loss Landscape. Trans. Mach. Learn. Res. 2024 (2024)
Kathlén Kohn, Guido Montúfar, Vahid Shahverdi, Matthew Trager
Function Space and Critical Points of Linear Convolutional Networks. SIAM J. Appl. Algebra Geom. 8 (2) (2024)
Shuang Liang, Renata Turkes, Jiayi Li, Nina Otter, Guido Montúfar
Pull-back Geometry of Persistent Homology Encodings. Trans. Mach. Learn. Res. 2024 (2024)
Marie-Charlotte Brandenburg, Georg Loho, Guido Montúfar
The Real Tropical Geometry of Neural Networks. CoRR (2024)
Mareike Dressler, Marina Garrote-López, Guido Montúfar, Johannes Müller, Kemal Rose
Algebraic optimization of sequential decision problems. J. Symb. Comput. 121 (2024)
Johannes Müller, Semih Cayci, Guido Montúfar
Fisher-Rao Gradient Flows of Linear Programs and State-Action Natural Policy Gradients. CoRR (2024)
Kedar Karhadkar, Erin George, Michael Murray, Guido Montúfar, Deanna Needell
Benign overfitting in leaky ReLU networks with moderate input dimension. CoRR (2024)
Kedar Karhadkar, Michael Murray, Guido Montúfar
Bounds for the smallest eigenvalue of the NTK for arbitrary spherical data of arbitrary dimension. CoRR (2024)
Kedar Karhadkar, Pradeep Kr. Banerjee, Guido Montúfar
FoSR: First-order spectral rewiring for addressing oversquashing in GNNs. ICLR (2023)
Johannes Rauh, Pradeep Kr. Banerjee, Eckehard Olbrich, Guido Montúfar, Jürgen Jost
Continuity and additivity properties of information decompositions. Int. J. Approx. Reason. 161 (2023)
Hanna Tseran, Guido Montúfar
Expected Gradients of Maxout Networks and Consequences to Parameter Initialization. ICML (2023)
Pierre Bréchet, Katerina Papagiannouli, Jing An, Guido Montúfar
Critical Points and Convergence Analysis of Generative Deep Linear Networks Trained with Bures-Wasserstein Loss. ICML (2023)
Michael Murray, Hui Jin, Benjamin Bowman, Guido Montúfar
Characterizing the spectrum of the NTK via a power series expansion. ICLR (2023)
Pierre Bréchet, Katerina Papagiannouli, Jing An, Guido Montúfar
Critical Points and Convergence Analysis of Generative Deep Linear Networks Trained with Bures-Wasserstein Loss. CoRR (2023)
Hui Jin, Guido Montúfar
Implicit Bias of Gradient Descent for Mean Squared Error Regression with Two-Layer Wide Neural Networks. J. Mach. Learn. Res. 24 (2023)
Kathlén Kohn, Guido Montúfar, Vahid Shahverdi, Matthew Trager
Function Space and Critical Points of Linear Convolutional Networks. CoRR (2023)
Kedar Karhadkar, Michael Murray, Hanna Tseran, Guido Montúfar
Mildly Overparameterized ReLU Networks Have a Favorable Loss Landscape. CoRR (2023)
Rishi Sonthalia, Anna Seigal, Guido Montúfar
Supermodular Rank: Set Function Decomposition and Optimization. CoRR (2023)
Hanna Tseran, Guido Montúfar
Expected Gradients of Maxout Networks and Consequences to Parameter Initialization. CoRR (2023)
Kathlén Kohn, Thomas Merkh, Guido Montúfar, Matthew Trager
Geometry of Linear Convolutional Networks. SIAM J. Appl. Algebra Geom. 6 (3) (2022)
Pradeep Kr. Banerjee, Kedar Karhadkar, Yu Guang Wang, Uri Alon, Guido Montúfar
Oversquashing in GNNs through the lens of information contraction and graph expansion. CoRR (2022)
Laura Escobar, Patricio Gallardo, Javier González-Anaya, José L. González, Guido Montúfar, Alejandro H. Morales
Enumeration of max-pooling responses with generalized permutohedra. CoRR (2022)
Kedar Karhadkar, Pradeep Kr. Banerjee, Guido Montúfar
FoSR: First-order spectral rewiring for addressing oversquashing in GNNs. CoRR (2022)
Johannes Müller, Guido Montúfar
The Geometry of Memoryless Stochastic Policy Optimization in Infinite-Horizon POMDPs. ICLR (2022)
Michael Murray, Hui Jin, Benjamin Bowman, Guido Montúfar
Characterizing the Spectrum of the NTK via a Power Series Expansion. CoRR (2022)
Renata Turkes, Guido Montúfar, Nina Otter
On the effectiveness of persistent homology. CoRR (2022)
Benjamin Bowman, Guido Montúfar
Implicit Bias of MSE Gradient Optimization in Underparameterized Neural Networks. ICLR (2022)
Johannes Müller, Guido Montúfar
Geometry and convergence of natural policy gradient methods. CoRR (2022)
Pradeep Kr. Banerjee, Kedar Karhadkar, Yuguang Wang, Uri Alon, Guido Montúfar
Oversquashing in GNNs through the lens of information contraction and graph expansion. Allerton (2022)
Guido Montúfar, Yue Ren, Leon Zhang
Sharp Bounds for the Number of Regions of Maxout Networks and Vertices of Minkowski Sums. SIAM J. Appl. Algebra Geom. 6 (1) (2022)
Benjamin Bowman, Guido Montúfar
Implicit Bias of MSE Gradient Optimization in Underparameterized Neural Networks. CoRR (2022)
Hui Jin, Pradeep Kr. Banerjee, Guido Montúfar
Learning Curves for Gaussian Process Regression with Power-Law Priors and Targets. ICLR (2022)
Guido Montúfar, Yu Guang Wang
Distributed Learning via Filtered Hyperinterpolation on Manifolds. Found. Comput. Math. 22 (4) (2022)
Johannes Müller, Guido Montúfar
Solving infinite-horizon POMDPs with memoryless stochastic policies in state-action space. CoRR (2022)
Johannes Rauh, Pradeep Kr. Banerjee, Eckehard Olbrich, Guido Montúfar, Jürgen Jost
Continuity and Additivity Properties of Information Decompositions. CoRR (2022)
Mareike Dressler, Marina Garrote-López, Guido Montúfar, Johannes Müller, Kemal Rose
Algebraic optimization of sequential decision problems. CoRR (2022)
Benjamin Bowman, Guido Montúfar
Spectral Bias Outside the Training Set for Deep Networks in the Kernel Regime. CoRR (2022)
Pradeep Kr. Banerjee, Guido Montúfar
Information Complexity and Generalization Bounds. ISIT (2021)
Hui Jin, Pradeep Kr. Banerjee, Guido Montúfar
Learning curves for Gaussian process regression with power-law priors and targets. CoRR (2021)
Johannes Müller, Guido Montúfar
The Geometry of Memoryless Stochastic Policy Optimization in Infinite-Horizon POMDPs. CoRR (2021)
Cristian Bodnar, Fabrizio Frasca, Nina Otter, Yu Guang Wang, Pietro Liò, Guido Montúfar, Michael M. Bronstein
Weisfeiler and Lehman Go Cellular: CW Networks. CoRR (2021)
Alex Tong Lin, Wuchen Li, Stanley J. Osher, Guido Montúfar
Wasserstein Proximal of GANs. GSI (2021)
Hanna Tseran, Guido Montúfar
On the Expected Complexity of Maxout Networks. CoRR (2021)
Pradeep Kr. Banerjee, Guido Montúfar
Information Complexity and Generalization Bounds. CoRR (2021)
Hanna Tseran, Guido Montúfar
On the Expected Complexity of Maxout Networks. NeurIPS (2021)
Alex Tong Lin, Wuchen Li, Stanley J. Osher, Guido Montúfar
Wasserstein Proximal of GANs. CoRR (2021)
Kathlén Kohn, Thomas Merkh, Guido Montúfar, Matthew Trager
Geometry of Linear Convolutional Networks. CoRR (2021)
Xuebin Zheng, Bingxin Zhou, Junbin Gao, Yuguang Wang, Pietro Lió, Ming Li, Guido Montúfar
How Framelets Enhance Graph Neural Networks. ICML (2021)
Alex Tong Lin, Mark J. Debord, Katia Estabridis, Gary A. Hewer, Guido Montúfar, Stanley J. Osher
Decentralized Multi-Agents by Imitation of a Centralized Controller. MSML (2021)
Cristian Bodnar, Fabrizio Frasca, Yu Guang Wang, Nina Otter, Guido Montúfar, Pietro Liò, Michael M. Bronstein
Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks. CoRR (2021)
Xuebin Zheng, Bingxin Zhou, Junbin Gao, Yu Guang Wang, Pietro Liò, Ming Li, Guido Montúfar
How Framelets Enhance Graph Neural Networks. CoRR (2021)
Guido Montúfar, Yue Ren, Leon Zhang
Sharp bounds for the number of regions of maxout networks and vertices of Minkowski sums. CoRR (2021)
Türkü Özlüm Çelik, Asgar Jamneshan, Guido Montúfar, Bernd Sturmfels, Lorenzo Venturello
Wasserstein distance to independence models. J. Symb. Comput. 104 (2021)
Dohyun Kwon, Yeoneung Kim, Guido Montúfar, Insoon Yang
Training Wasserstein GANs without gradient penalties. CoRR (2021)
Quynh Nguyen, Marco Mondelli, Guido Montúfar
Tight Bounds on the Smallest Eigenvalue of the Neural Tangent Kernel for Deep ReLU Networks. CoRR (2020)
Yonatan Dukler, Quanquan Gu, Guido Montúfar
Optimization Theory for ReLU Neural Networks Trained with Normalization Layers. ICML (2020)
Guido Montúfar, Nina Otter, Yuguang Wang
Can neural networks learn persistent homology features? CoRR (2020)
Guido Montúfar, Yu Guang Wang
Distributed Learning via Filtered Hyperinterpolation on Manifolds. CoRR (2020)
Pradeep Kr. Banerjee, Guido Montúfar
The Variational Deficiency Bottleneck. IJCNN (2020)
Yuguang Wang, Ming Li, Zheng Ma, Guido Montúfar, Xiaosheng Zhuang, Yanan Fan
Haar Graph Pooling. ICML (2020)
Yonatan Dukler, Quanquan Gu, Guido Montúfar
Optimization Theory for ReLU Neural Networks Trained with Normalization Layers. CoRR (2020)
Thomas Merkh, Guido Montúfar
Factorized mutual information maximization. Kybernetika 56 (5) (2020)
Hui Jin, Guido Montúfar
Implicit bias of gradient descent for mean squared error regression with wide neural networks. CoRR (2020)
Michael Arbel, Arthur Gretton, Wuchen Li, Guido Montúfar
Kernelized Wasserstein Natural Gradient. ICLR (2020)
Thomas Merkh, Guido Montúfar
Factorized Mutual Information Maximization. CoRR (2019)
Thomas Merkh, Guido Montúfar
Stochastic Feedforward Neural Networks: Universal Approximation. CoRR (2019)
Michael Arbel, Arthur Gretton, Wuchen Li, Guido Montúfar
Kernelized Wasserstein Natural Gradient. CoRR (2019)
Yonatan Dukler, Wuchen Li, Alex Tong Lin, Guido Montúfar
Wasserstein of Wasserstein Loss for Learning Generative Models. ICML (2019)
Yu Guang Wang, Ming Li, Zheng Ma, Guido Montúfar, Xiaosheng Zhuang, Yanan Fan
HaarPooling: Graph Pooling with Compressive Haar Basis. CoRR (2019)
Wuchen Li, Alex Tong Lin, Guido Montúfar
Affine Natural Proximal Learning. GSI (2019)
Anton Mallasto, Guido Montúfar, Augusto Gerolin
How Well Do WGANs Estimate the Wasserstein Metric? CoRR (2019)
Türkü Özlüm Çelik, Asgar Jamneshan, Guido Montúfar, Bernd Sturmfels, Lorenzo Venturello
Optimal Transport to a Variety. MACIS (2019)
Alex Tong Lin, Yonatan Dukler, Wuchen Li, Guido Montúfar
Wasserstein Diffusion Tikhonov Regularization. CoRR (2019)
Guido Montúfar
Restricted Boltzmann Machines: Introduction and Review. CoRR (2018)
Wuchen Li, Guido Montúfar
Ricci curvature for parametric statistics via optimal transport. CoRR (2018)
Pradeep Kr. Banerjee, Johannes Rauh, Guido Montúfar
Computing the Unique Information. ISIT (2018)
Pradeep Kr. Banerjee, Guido Montúfar
The Variational Deficiency Bottleneck. CoRR (2018)
Wuchen Li, Guido Montúfar
Natural gradient via optimal transport I. CoRR (2018)
Guido Montúfar, Johannes Rauh
Geometry of Policy Improvement. CoRR (2017)
Keyan Ghazi-Zahedi, Raphael Deimel, Guido Montúfar, Vincent Wall, Oliver Brock
Morphological computation: The good, the bad, and the ugly. IROS (2017)
Guido Montúfar, Johannes Rauh
Geometry of Policy Improvement. GSI (2017)
Pradeep Kr. Banerjee, Johannes Rauh, Guido Montúfar
Computing the Unique Information. CoRR (2017)
Guido Montúfar, Jason Morton
Dimension of Marginals of Kronecker Product Models. SIAM J. Appl. Algebra Geom. 1 (1) (2017)
Guido Montúfar, Johannes Rauh
Hierarchical models as marginals of hierarchical models. Int. J. Approx. Reason. 88 (2017)
Guido Montúfar, Keyan Ghazi-Zahedi, Nihat Ay
Information Theoretically Aided Reinforcement Learning for Embodied Agents. CoRR (2016)
Keyan Ghazi-Zahedi, Daniel F. B. Haeufle, Guido Montúfar, Syn Schmitt, Nihat Ay
Evaluating Morphological Computation in Muscle and DC-Motor Driven Models of Hopping Movements. Frontiers Robotics AI 3 (2016)
Guido Montúfar
Universal Approximation of Markov Kernels by Shallow Stochastic Feedforward Networks. CoRR (2015)
Guido Montúfar, Keyan Ghazi-Zahedi, Nihat Ay
Geometry and Determinism of Optimal Stationary Control in Partially Observable Markov Decision Processes. CoRR (2015)
Keyan Ghazi-Zahedi, Daniel F. B. Haeufle, Guido Montúfar, Syn Schmitt, Nihat Ay
Evaluating Morphological Computation in Muscle and DC-motor Driven Models of Human Hopping. CoRR (2015)
Guido Montúfar, Nihat Ay, Keyan Ghazi-Zahedi
Geometry and expressive power of conditional restricted Boltzmann machines. J. Mach. Learn. Res. 16 (2015)
Guido Montúfar, Johannes Rauh
Hierarchical Models as Marginals of Hierarchical Models. CoRR (2015)
Guido Montúfar, Jason Morton
Dimension of Marginals of Kronecker Product Models. CoRR (2015)
Guido Montúfar, Jason Morton
Discrete restricted Boltzmann machines. J. Mach. Learn. Res. 16 (2015)
Guido Montúfar, Keyan Ghazi-Zahedi, Nihat Ay
A Theory of Cheap Control in Embodied Systems. PLoS Comput. Biol. 11 (9) (2015)
Guido Montúfar
Deep Narrow Boltzmann Machines are Universal Approximators. ICLR (Poster) (2015)
Guido Montúfar, Nihat Ay, Keyan Zahedi
Expressive Power of Conditional Restricted Boltzmann Machines for Sensorimotor Control. CoRR (2014)
Tyll Krueger, Guido Montúfar, Ruedi Seiler, Rainer Siegmund-Schultze
Sequential Recurrence-Based Multidimensional Universal Source Coding of Lempel-Ziv Type. CoRR (2014)
Razvan Pascanu, Guido Montúfar, Yoshua Bengio
On the number of inference regions of deep feed forward networks with piece-wise linear activations. ICLR (Poster) (2014)
Guido Montúfar, Nihat Ay, Keyan Ghazi-Zahedi
A Framework for Cheap Universal Approximation in Embodied Systems. CoRR (2014)
Tyll Krüger, Guido Montúfar, Ruedi Seiler, Rainer Siegmund-Schultze
Universally typical sets for ergodic sources of multidimensional data. Kybernetika 49 (6) (2013)

Guido Montúfar.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Guido Montúfar