Aranyak Acharyya

Statistics and Probability · 2024–2026

A researcher in the Science corpus: 6 papers; trusts 3 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 15 citations into it; #10,838 of 12,932 by trust here, #4,371 by citations
• Representation & Self-Supervised Learning — 13 citations into it

Whom Aranyak Acharyya trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Joseph B. Kruskal
2. Hayden S. Helm
3. Brandon Duderstadt
4. Zach Nussbaum
5. Carey E. Priebe
6. John X. Morris
7. Youngser Park
8. I. Borg

Who trusts Aranyak Acharyya overall

1. Hayden S. Helm
2. Carey E. Priebe

Papers from Aranyak Acharyya's perspective

Ordered by how strongly the researchers Aranyak Acharyya trusts endorse each paper. Same corpus, a different order for every researcher.

1. Attention is All you Need (Neural Information Processing Systems)
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. Learning Multiple Layers of Features from Tiny Images
9. Language Models are Few-Shot Learners (Neural Information Processing Systems)
10. ImageNet: A large-scale hierarchical image database

Their papers

• Recovering manifold structure in LLM responses through a joint Euclidean mirror (2026)
• Testing for LLM response differences: the case of a composite null consisting of semantically irrelevant query perturbations (2025)
• Concentration bounds on response-based vector embeddings of black-box generative models (2025)
• Convergence Guarantees for Response Prediction for Latent Structure Network Time Series (2025)
• Consistent estimation of generative model representations in the data kernel perspective space (2024)
• Statistical inference on black-box generative models in the data kernel perspective space (2024) — 12 citations