Srinivas Anumasa

20 papers A* 3A 2Journal 12Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	AI-generated data contamination erodes pathological variability and diagnostic reliability. CoRR Hongyu He, Shaowen Xiang, Ye Zhang, Yingtao Zhu, Jin Zhang, Hao Deng, Emily Alsentzer, Yun Liu, Qingyu Chen, Kun-Hsing Yu, Andrew Marshall, Tingting Chen, Srinivas Anumasa, Daniel Ebner, Dean Ho, Kee Yuan Ngiam, Ching-Yu Cheng, Dianbo Liu
2026	J	`jnl`	Navigating heterogeneous protein landscapes through geometry-aware smoothing. CoRR Srinivas Anumasa, Barath Chandran. C, Tingting Chen, Nuwaisir Mohammad Rahman, Yingtao Zhu, Rushi Shah, Hongyu He, Peisong Zhang, Yizhen Liao, Yiming Tang, Yong Shen, Tianfan Fu, Rui Qing, Xiao Li, Sebastian Maurer-Stroh, Xinyi Su, ZhiZhuo Zhang, Dianbo Liu
2025	J	`jnl`	Auto-Bench: An Automated Benchmark for Scientific Discovery in LLMs. CoRR Tingting Chen, Srinivas Anumasa, Beibei Lin, Vedant Shah, Anirudh Goyal, Dianbo Liu
2025	J	`jnl`	Data-Dependent Smoothing for Protein Discovery with Walk-Jump Sampling. CoRR Srinivas Anumasa, Barath Chandran. C, Tingting Chen, Dianbo Liu
2025	J	`jnl`	Interpretable Evaluation of AI-Generated Content with Language-Grounded Sparse Encoders. CoRR Yiming Tang, Arash Lagzian, Srinivas Anumasa, Qiran Zou, Trang Nguyen, Ehsan Adeli, Ching-Yu Cheng, Yilun Du, Dianbo Liu
2025	J	`jnl`	Laplacian Score Sharpening for Mitigating Hallucination in Diffusion Models. CoRR Barath Chandran. C, Srinivas Anumasa, Dianbo Liu
2025	J	`jnl`	Multi-Novelty: Improve the Diversity and Novelty of Contents Generated by Large Language Models via inference-time Multi-Views Brainstorming. CoRR Arash Lagzian, Srinivas Anumasa, Dianbo Liu
2024	A	`conf`	Data Driven Threshold and Potential Initialization for Spiking Neural Networks. AISTATS Velibor Bojkovic, Srinivas Anumasa, Giulia De Masi, Bin Gu, Huan Xiong
2024	A*	`conf`	Enhancing Training of Spiking Neural Network with Stochastic Latency. AAAI Srinivas Anumasa, Bhaskar Mukhoty, Velibor Bojkovic, Giulia De Masi, Huan Xiong, Bin Gu
2023	A*	`conf`	A Unified Optimization Framework of ANN-SNN Conversion: Towards Optimal Mapping from Activation Values to Firing Rates. ICML Haiyan Jiang, Srinivas Anumasa, Giulia De Masi, Huan Xiong, Bin Gu
2023	—	`conf`	Continuous Depth Recurrent Neural Differential Equations. ECML/PKDD (2) Srinivas Anumasa, Geetakrishnasai Gunapati, P. K. Srijith
2022	J	`jnl`	Continuous Depth Recurrent Neural Differential Equations. CoRR Srinivas Anumasa, Geetakrishnasai Gunapati, P. K. Srijith
2022	A*	`conf`	Latent Time Neural Ordinary Differential Equations. AAAI Srinivas Anumasa, P. K. Srijith
2021	J	`jnl`	Bi-Directional Recurrent Neural Ordinary Differential Equations for Social Media Text Classification. CoRR Maunika Tamire, Srinivas Anumasa, P. K. Srijith
2021	—	`conf`	Delay Differential Neural Networks. ICMLT Srinivas Anumasa, P. K. Srijith
2021	A	`conf`	Improving Robustness and Uncertainty Modelling in Neural Ordinary Differential Equations. WACV Srinivas Anumasa, P. K. Srijith
2021	J	`jnl`	Improving Robustness and Uncertainty Modelling in Neural Ordinary Differential Equations. CoRR Srinivas Anumasa, P. K. Srijith
2021	J	`jnl`	Latent Time Neural Ordinary Differential Equations. CoRR Srinivas Anumasa, P. K. Srijith
2020	—	`conf`	Decision Making under Uncertainty with Convolutional Deep Gaussian Processes. COMAD/CODS Dinesh Jain, Srinivas Anumasa, P. K. Srijith
2020	J	`jnl`	Delay Differential Neural Networks. CoRR Srinivas Anumasa, P. K. Srijith