Siddhartha Mishra
20 papers · 2021–2024 · 7 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+8 more ↓ Show less ↑
🐣 Hot Topic Early Bird 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (46) 👑 Triple Crown
🏆
Keyword Champion
(9)
🏆
Grand Slam
🧭
Keyword Pioneer
👥
Mega-Team · Squad
⚡
Prolific Year · Productive
🗃️
Keyword Collector
(93)
📈
Trend Setter
💎
Century Club · Bronze
Top co-authors
Research topics
Machine Learning
(19)
Deep Learning
(16)
Architectures
(11)
Optimization & Theory · Machine Learning
(9)
Mathematics & Optimization
(8)
Core Methods
(8)
Artificial Intelligence
(7)
Core AI
(6)
Learning Types · Machine Learning
(5)
Mathematics
(5)
Models
(5)
Optimization
(5)
Optimization & Theory · Deep Learning
(5)
Application Areas
(3)
Learning Types · Deep Learning
(3)
Keywords
partial differential equation
(9)
operator learning
(7)
neural operator
(4)
recurrent neural network
(3)
fourier neural operator
(3)
universal approximation
(2)
graph neural network
(2)
foundation model
(2)
sequence modeling
(2)
gradient propagation
(2)
physics-informed neural network
(2)
coupled oscillator
(2)
deep learning
(1)
instruction following
(1)
natural language processing
(1)
language modeling
(1)
transfer learning
(1)
zero-shot learning
(1)
in-context learning
(1)
rand index
(1)
Papers
An operator preconditioning perspective on training in physics-informed machine learning
ICLR 2024
Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary Domains
ICML 2024
FUSE: Fast Unified Simulation and Estimation for PDEs
NeurIPS 2024
Poseidon: Efficient Foundation Models for PDEs
NeurIPS 2024
SmallToLarge (S2L): Scalable Data Selection for Fine-tuning Large Language Models by Summarizing Training Trajectories of Small Models
NeurIPS 2024
Convolutional Neural Operators for robust and accurate learning of PDEs
NeurIPS 2023
Gradient Gating for Deep Multi-Rate Learning on Graphs
ICLR 2023
Neural Inverse Operators for Solving PDE Inverse Problems
ICML 2023
Neural Oscillators are Universal
NeurIPS 2023
Nonlinear Reconstruction for Operator Learning of PDEs with Discontinuities
ICLR 2023
Representation Equivalent Neural Operators: a Framework for Alias-free Operator Learning
NeurIPS 2023
An Evaluative Measure of Clustering Methods Incorporating Hyperparameter Sensitivity
AAAI 2022
Generic bounds on the approximation error for physics-informed (and) operator learning
NeurIPS 2022
Graph-Coupled Oscillator Networks
ICML 2022
Long Expressive Memory for Sequence Modeling
ICLR 2022
Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks
EMNLP 2022
Word2Box: Capturing Set-Theoretic Semantics of Words using Box Embeddings
ACL 2022
Coupled Oscillatory Recurrent Neural Network (coRNN): An accurate and (gradient) stable architecture for learning long time dependencies
ICLR 2021
On Universal Approximation and Error Bounds for Fourier Neural Operators
JMLR 2021
UnICORNN: A recurrent model for learning very long time dependencies
ICML 2021