Leena Chennuru Vankadara

Quzhou College of Technology — China

Computer Science · Physical Sciences

3h-index45citations26works0.12yr avg
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Research Topics

Advanced Graph Neural Networks(4), Face and Expression Recognition(3), Statistical Methods and Inference(3), Bayesian Modeling and Causal Inference(3), Bayesian Methods and Mixture Models(3)

Publications25 total

Training Neural Networks at Any Scale
arXiv (Cornell University)·2025Open Access
On the Surprising Effectiveness of Large Learning Rates under Standard Width Scaling
arXiv (Cornell University)·2025Open Access
μP$^2$: Effective Sharpness Aware Minimization Requires Layerwise Perturbation Scaling
arXiv (Cornell University)·2024Open Access
A consistent estimator for confounding strength
Mathematical Statistics and Learning·2024Open Access
Explaining Kernel Clustering via Decision Trees
arXiv (Cornell University)·2024Open Access
$\boldsymbol{\mu}\mathbf{P^2}$: Effective Sharpness Aware Minimization Requires Layerwise Perturbation Scaling
2024
On Feature Learning in Structured State Space Models
2024
Self-Compatibility: Evaluating Causal Discovery without Ground Truth
arXiv (Cornell University)·2023· 1 citedOpen Access
Reinterpreting causal discovery as the task of predicting unobserved joint statistics
arXiv (Cornell University)·2023Open Access
A Consistent Estimator for Confounding Strength
arXiv (Cornell University)·2022· 1 citedOpen Access
Interpolation and Regularization for Causal Learning
arXiv (Cornell University)·2022Open Access
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural Networks
arXiv (Cornell University)·2021· 3 citedOpen Access
Learning Theory Can (Sometimes) Explain Generalisation in Graph Neural\n Networks
arXiv (Cornell University)·2021· 6 citedOpen Access
Causal Forecasting:Generalization Bounds for Autoregressive Models
arXiv (Cornell University)·2021Open Access
Recovery Guarantees for Kernel-based Clustering under Non-parametric Mixture Models
arXiv (Cornell University)·2021Open Access
Recovery Guarantees for Kernel-based Clustering under Non-parametric\n Mixture Models
arXiv (Cornell University)·2021Open Access
Graphon based Clustering and Testing of Networks: Algorithms and Theory
arXiv (Cornell University)·2021· 1 citedOpen Access
Large scale ordinal embedding: training neural networks with structure-free inputs
arXiv (Cornell University)·2019· 1 citedOpen Access
Insights into Ordinal Embedding Algorithms: A Systematic Evaluation
arXiv (Cornell University)·2019· 1 citedOpen Access
On the optimality of kernels for high-dimensional clustering
arXiv (Cornell University)·2019· 3 citedOpen Access
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Frequent Co-authors

Debarghya Ghoshdastidar(11), Ulrike von Luxburg(10), Faiz Ul Wahab(5), Moritz Haas(4), Volkan Cevher(4), Iris Wieser(3), Sibel Toprak(3), Andreas Grenzing(3), Tobias Hinz(3), Sayantan Auddy(3), Ethem Can Karaoğuz(3), Abhilash Chandran(3), Melanie Remmels(3), Abdelaziz El Shinawi(3), Josip Josifovski(3), Debasish Sahu(3), Stefan Heinrich(3), Nicolás Navarro-Guerrero(3), Erik Strahl(3), Johannes Twiefel(3)