Clayton Sanford
Publications by Year
Research Areas
Neural Networks and Applications, Stochastic Gradient Optimization Techniques, Advanced Memory and Neural Computing, Model Reduction and Neural Networks, Sparse and Compressive Sensing Techniques
Most-Cited Works
- → Representational Strengths and Limitations of Transformers(2023)12 cited
- → Learning Single-Index Models with Shallow Neural Networks(2022)11 cited
- → Enabling Equation-Free Modeling via Diffusion Maps(2022)8 cited
- → Understanding Transformer Reasoning Capabilities via Graph Algorithms(2024)5 cited
- → Support vector machines and linear regression coincide with very high-dimensional features(2021)4 cited
- → Transformers, parallel computation, and logarithmic depth(2024)2 cited
- → Improving the predictions of ML-corrected climate models with novelty detection(2022)2 cited
- → On the Approximation Power of Two-Layer Networks of Random ReLUs(2021)2 cited
- → Best of Both Worlds: Advantages of Hybrid Graph Sequence Models(2024)1 cited