Parikshit Ram

Computer Science · Physical Sciences

16h-index1.3kcitations94works0.52yr avg
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Research Topics

Machine Learning and Data Classification(29), Machine Learning and Algorithms(17), Advanced Image and Video Retrieval Techniques(12), Domain Adaptation and Few-Shot Learning(11), Algorithms and Data Compression(10)

Publications94 total

Deep Clustering with Associative Memories
ArXiv.org·2026Open Access
Deep Clustering with Associative Memories
arXiv (Cornell University)·2026Open Access
Mitigating Modality Imbalance in Multi-modal Learning via Multi-objective Optimization
arXiv (Cornell University)·2025Open Access
Quantifying artificial intelligence through algorithmic generalization
Nature Machine Intelligence·2025· 2 cited
Finding Clustering Algorithms in the Transformer Architecture
arXiv (Cornell University)·2025Open Access
Transformers Learn Faster with Semantic Focus
arXiv (Cornell University)·2025Open Access
Reasoning Model Unlearning: Forgetting Traces, Not Just Answers, While Preserving Reasoning Skills
arXiv (Cornell University)·2025Open Access
Dense Associative Memory with Epanechnikov Energy
arXiv (Cornell University)·2025Open Access
Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning
arXiv (Cornell University)·2025Open Access
Neural Reasoning Networks: Efficient Interpretable Neural Networks with Automatic Textual Explanations
Proceedings of the AAAI Conference on Artificial Intelligence·2025Open Access
On Learning Representations for Tabular Data Distillation
arXiv (Cornell University)·2025Open Access
Reasoning Model Unlearning: Forgetting Traces, Not Just Answers, While Preserving Reasoning Skills
2025Open Access
American Sign Language (ASL) Hand Sign Detection on Raspberry Pi Using Deep Learning Techniques
2024· 1 cited
Quantifying artificial intelligence through algorithmic generalization
arXiv (Cornell University)·2024Open Access
Dense Associative Memory Through the Lens of Random Features
arXiv (Cornell University)·2024· 1 citedOpen Access
WAGLE: Strategic Weight Attribution for Effective and Modular Unlearning in Large Language Models
arXiv (Cornell University)·2024· 1 citedOpen Access
Understanding Forgetting in LLM Supervised Fine-Tuning and Preference Learning -- A Convex Optimization Perspective
arXiv (Cornell University)·2024· 1 citedOpen Access
Neural Reasoning Networks: Efficient Interpretable Neural Networks With Automatic Textual Explanations
arXiv (Cornell University)·2024Open Access
Long-Term Individual Causal Effect Estimation via Identifiable Latent Representation Learning
2024· 2 citedOpen Access
Byzantine-Resilient Bilevel Federated Learning
2024· 1 cited
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Frequent Co-authors

Alexander Gray(19), Horst Samulowitz(12), Sijia Liu(8), Djallel Bouneffouf(8), Dakuo Wang(6), K. P. Sinha(6), Martin Hirzel(5), Kiran Kate(5), Avraham Shinnar(5), Ryan R. Curtin(4), William B. March(4), Gregory Bramble(4), Ambrish Rawat(4), Martin Wistuba(4), Justin D. Weisz(3), Michael Müller(3), Deepak Vijaykeerthy(3), Dongryeol Lee(3), Yuguang Yao(3), Sijia Liu(3)