77 citations · 169 across the 26 of their papers we have counts for
20 papers · 1 filter
Neural PDE Solvers for Irregular Domains
Biswajit Khara, Ethan Herron, Zhanhong Jiang +8
Neural network-based approaches for solving partial differential equations (PDEs) have recently received special attention. However, the large majority of neural PDE solvers only a…
Distributed Online Non-convex Optimization with Composite Regret
Zhanhong Jiang, Aditya Balu, Xian Yeow Lee +3
Regret has been widely adopted as the metric of choice for evaluating the performance of online optimization algorithms for distributed, multi-agent systems. However, data/model va…
On The Computational Complexity of Self-Attention
Feyza Duman Keles, Pruthuvi Mahesakya Wijewardena, Chinmay Hegde
Transformer architectures have led to remarkable progress in many state-of-art applications. However, despite their successes, modern transformers rely on the self-attention mechan…
Smooth-Reduce: Leveraging Patches for Improved Certified Robustness
Ameya Joshi, Minh Pham, Minsu Cho +4
Randomized smoothing (RS) has been shown to be a fast, scalable technique for certifying the robustness of deep neural network classifiers. However, methods based on RS require aug…
NeuFENet: Neural Finite Element Solutions with Theoretical Bounds for Parametric PDEs
Biswajit Khara, Aditya Balu, Ameya Joshi +4
We consider a mesh-based approach for training a neural network to produce field predictions of solutions to parametric partial differential equations (PDEs). This approach contras…
Differentiable Spline Approximations
Minsu Cho, Aditya Balu, Ameya Joshi +6
The paradigm of differentiable programming has significantly enhanced the scope of machine learning via the judicious use of gradient-based optimization. However, standard differen…