David W. Romero

39 papers A* 12Journal 24Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Cosmos-Reason1: From Physical Common Sense To Embodied Reasoning. CoRR Alisson G. Azzolini, Hannah Brandon, Prithvijit Chattopadhyay, Huayu Chen, Jinju Chu, Yin Cui, Jenna Diamond, Yifan Ding, Francesco Ferroni, Rama Govindaraju, Jinwei Gu, Siddharth Gururani, Imad El Hanafi, Zekun Hao, Jacob Samuel Huffman, Jingyi Jin, Brendan Johnson, Rizwan Khan, George Kurian, Elena Lantz, Nayeon Lee, Zhaoshuo Li, Xuan Li, Tsung-Yi Lin, Yen-Chen Lin, Ming-Yu Liu, Alice Luo, Andrew Mathau, Yun Ni, Lindsey Pavao, Wei Ping, David W. Romero, Misha Smelyanskiy, Shuran Song, Lyne Tchapmi, Andrew Z. Wang, Boxin Wang, Haoxiang Wang, Fangyin Wei, Jiashu Xu, Yao Xu, Xiaodong Yang, Zhuolin Yang, Xiaohui Zeng, Zhe Zhang
2025	A*	`conf`	HMAR: Efficient Hierarchical Masked Auto-Regressive Image Generation. CVPR Hermann Kumbong, Xian Liu, Tsung-Yi Lin, Ming-Yu Liu, Xihui Liu, Ziwei Liu, Daniel Y. Fu, Christopher Ré, David W. Romero
2025	J	`jnl`	HMAR: Efficient Hierarchical Masked Auto-Regressive Image Generation. CoRR Hermann Kumbong, Xian Liu, Tsung-Yi Lin, Ming-Yu Liu, Xihui Liu, Ziwei Liu, Daniel Y. Fu, Christopher Ré, David W. Romero
2025	J	`jnl`	MFM-point: Multi-scale Flow Matching for Point Cloud Generation. CoRR Petr Molodyk, Jaemoo Choi, David W. Romero, Ming-Yu Liu, Yongxin Chen
2025	J	`jnl`	RECON: Robust symmetry discovery via Explicit Canonical Orientation Normalization. CoRR Alonso Urbano, David W. Romero, Max Zimmer, Sebastian Pokutta
2025	J	`jnl`	Systems and Algorithms for Convolutional Multi-Hybrid Language Models at Scale. CoRR Jerome Ku, Eric Nguyen, David W. Romero, Garyk Brixi, Brandon Yang, Anton Vorontsov, Ali Taghibakhshi, Amy X. Lu, Dave P. Burke, Greg Brockman, Stefano Massaroli, Christopher Ré, Patrick D. Hsu, Brian L. Hie, Stefano Ermon, Michael Poli
2024	A*	`conf`	Fast, Expressive SE(n) Equivariant Networks through Weight-Sharing in Position-Orientation Space. ICLR Erik J. Bekkers, Sharvaree P. Vadgama, Rob Hesselink, Putri A. van der Linden, David W. Romero
2024	J	`jnl`	Meshtron: High-Fidelity, Artist-Like 3D Mesh Generation at Scale. CoRR Zekun Hao, David W. Romero, Tsung-Yi Lin, Ming-Yu Liu
2024	—	`conf`	Self-supervised detection of perfect and partial input-dependent symmetries. GRaM Alonso Urbano, David W. Romero
2024	J	`jnl`	The Good, The Efficient and the Inductive Biases: Exploring Efficiency in Deep Learning Through the Use of Inductive Biases. CoRR David W. Romero
2024	J	`jnl`	Wavelet Networks: Scale-Translation Equivariant Learning From Raw Time-Series. Trans. Mach. Learn. Res. David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn
2023	J	`jnl`	DNArch: Learning Convolutional Neural Architectures by Backpropagation. CoRR David W. Romero, Neil Zeghidour
2023	J	`jnl`	Fast, Expressive SE(n) Equivariant Networks through Weight-Sharing in Position-Orientation Space. CoRR Erik J. Bekkers, Sharvaree P. Vadgama, Rob D. Hesselink, Putri A. van der Linden, David W. Romero
2023	A*	`conf`	Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions. NeurIPS Stefano Massaroli, Michael Poli, Daniel Y. Fu, Hermann Kumbong, Rom N. Parnichkun, David W. Romero, Aman Timalsina, Quinn McIntyre, Beidi Chen, Atri Rudra, Ce Zhang, Christopher Ré, Stefano Ermon, Yoshua Bengio
2023	J	`jnl`	Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions. CoRR Stefano Massaroli, Michael Poli, Daniel Y. Fu, Hermann Kumbong, Rom N. Parnichkun, Aman Timalsina, David W. Romero, Quinn McIntyre, Beidi Chen, Atri Rudra, Ce Zhang, Christopher Ré, Stefano Ermon, Yoshua Bengio
2023	—	`conf`	Learned Gridification for Efficient Point Cloud Processing. TAG-ML Putri A. van der Linden, David W. Romero, Erik J. Bekkers
2023	J	`jnl`	Learned Gridification for Efficient Point Cloud Processing. CoRR Putri A. van der Linden, David W. Romero, Erik J. Bekkers
2023	A*	`conf`	Modelling Long Range Dependencies in $N$D: From Task-Specific to a General Purpose CNN. ICLR David M. Knigge, David W. Romero, Albert Gu, Efstratios Gavves, Erik J. Bekkers, Jakub Mikolaj Tomczak, Mark Hoogendoorn, Jan-Jakob Sonke
2023	J	`jnl`	Modelling Long Range Dependencies in N-D: From Task-Specific to a General Purpose CNN. CoRR David M. Knigge, David W. Romero, Albert Gu, Efstratios Gavves, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn, Jan-Jakob Sonke
2023	J	`jnl`	Self-Supervised Detection of Perfect and Partial Input-Dependent Symmetries. CoRR Alonso Urbano, David W. Romero
2022	A*	`conf`	CKConv: Continuous Kernel Convolution For Sequential Data. ICLR David W. Romero, Anna Kuzina, Erik J. Bekkers, Jakub Mikolaj Tomczak, Mark Hoogendoorn
2022	A*	`conf`	Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups. ICML David M. Knigge, David W. Romero, Erik J. Bekkers
2022	A*	`conf`	FlexConv: Continuous Kernel Convolutions With Differentiable Kernel Sizes. ICLR David W. Romero, Robert-Jan Bruintjes, Jakub Mikolaj Tomczak, Erik J. Bekkers, Mark Hoogendoorn, Jan van Gemert
2022	A*	`conf`	Learning Partial Equivariances From Data. NeurIPS David W. Romero, Suhas Lohit
2022	A*	`conf`	Relaxing Equivariance Constraints with Non-stationary Continuous Filters. NeurIPS Tycho F. A. van der Ouderaa, David W. Romero, Mark van der Wilk
2022	J	`jnl`	Relaxing Equivariance Constraints with Non-stationary Continuous Filters. CoRR Tycho F. A. van der Ouderaa, David W. Romero, Mark van der Wilk
2022	J	`jnl`	Towards a General Purpose CNN for Long Range Dependencies in ND. CoRR David W. Romero, David M. Knigge, Albert Gu, Erik J. Bekkers, Efstratios Gavves, Jakub M. Tomczak, Mark Hoogendoorn
2021	J	`jnl`	CKConv: Continuous Kernel Convolution For Sequential Data. CoRR David W. Romero, Anna Kuzina, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn
2021	J	`jnl`	Exploiting Redundancy: Separable Group Convolutional Networks on Lie Groups. CoRR David M. Knigge, David W. Romero, Erik J. Bekkers
2021	J	`jnl`	FlexConv: Continuous Kernel Convolutions with Differentiable Kernel Sizes. CoRR David W. Romero, Robert-Jan Bruintjes, Jakub M. Tomczak, Erik J. Bekkers, Mark Hoogendoorn, Jan C. van Gemert
2021	A*	`conf`	Group Equivariant Stand-Alone Self-Attention For Vision. ICLR David W. Romero, Jean-Baptiste Cordonnier
2021	J	`jnl`	Learning Equivariances and Partial Equivariances from Data. CoRR David W. Romero, Suhas Lohit
2020	A*	`conf`	Attentive Group Equivariant Convolutional Networks. ICML David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn
2020	J	`jnl`	Attentive Group Equivariant Convolutional Networks. CoRR David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn
2020	A*	`conf`	Co-Attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-Occurring in Data. ICLR David W. Romero, Mark Hoogendoorn
2020	—	`conf`	Generative Fourier-Based Auto-encoders: Preliminary Results. LOD (2) Alessandro Zonta, Ali el Hassouni, David W. Romero, Jakub M. Tomczak
2020	J	`jnl`	Group Equivariant Stand-Alone Self-Attention For Vision. CoRR David W. Romero, Jean-Baptiste Cordonnier
2020	J	`jnl`	Wavelet Networks: Scale Equivariant Learning From Raw Waveforms. CoRR David W. Romero, Erik J. Bekkers, Jakub M. Tomczak, Mark Hoogendoorn
2019	J	`jnl`	Co-Attentive Equivariant Neural Networks: Focusing Equivariance On Transformations Co-Occurring In Data. CoRR David W. Romero, Mark Hoogendoorn