Aayush Mishra - RankMe

25 papers A* 3A 2Journal 18Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	BayesFlow 2.0: Multi-Backend Amortized Bayesian Inference in Python. CoRR Lars Kühmichel, Jerry M. Huang, Valentin Pratz, Jonas Arruda, Hans Olischläger, Daniel Habermann, Simon Kucharský, Lasse Elsemüller, Aayush Mishra, Niels Bracher, Svenja Jedhoff, Marvin Schmitt, Paul-Christian Bürkner, Stefan T. Radev
2026	J	`jnl`	Genomic Next-Token Predictors are In-Context Learners. Trans. Mach. Learn. Res. Nathan Breslow, Aayush Mishra, Michael C. Schatz, Anqi Liu, Mahler Revsine, Daniel Khashabi
2026	J	`jnl`	Unsupervised Continual Learning for Amortized Bayesian Inference. CoRR Aayush Mishra, Simon Kucharský, Paul-Christian Bürkner
2025	J	`jnl`	A Critical Review of IoT-Based Structural Health Monitoring for Dams. IEEE Internet Things J. Aajid Khan, Satanand Mishra, Shivani Pandey, Tanmay Sardar, Aayush Mishra, Manish Mudgal, Sandeep Singhai
2025	J	`jnl`	Automatic Machine Learning Framework to Study Morphological Parameters of AGN Host Galaxies within z < 1.4 in the Hyper Supreme-Cam Wide Survey. CoRR Chuan Tian, C. Megan Urry, Aritra Ghosh, Daisuke Nagai, Tonima Tasnim Ananna, Meredith C. Powell, Connor Auge, Aayush Mishra, David B. Sanders, Nico Cappelluti, Kevin Schawinski
2025	J	`jnl`	Genomic Next-Token Predictors are In-Context Learners. CoRR Nathan Breslow, Aayush Mishra, Mahler Revsine, Michael C. Schatz, Anqi Liu, Daniel Khashabi
2025	J	`jnl`	IA2: Alignment with ICL Activations Improves Supervised Fine-Tuning. CoRR Aayush Mishra, Daniel Khashabi, Anqi Liu
2025	A*	`conf`	ICL CIPHERS: Quantifying "Learning" in In-Context Learning via Substitution Ciphers. EMNLP Zhouxiang Fang, Aayush Mishra, Muhan Gao, Anqi Liu, Daniel Khashabi
2025	J	`jnl`	ICL CIPHERS: Quantifying "Learning" in In-Context Learning via Substitution Ciphers. CoRR Zhouxiang Fang, Aayush Mishra, Muhan Gao, Anqi Liu, Daniel Khashabi
2025	A	`conf`	ODD: Overlap-aware Estimation of Model Performance under Distribution Shift. UAI Aayush Mishra, Anqi Liu
2025	J	`jnl`	ODD: Overlap-aware Estimation of Model Performance under Distribution Shift. CoRR Aayush Mishra, Anqi Liu
2025	J	`jnl`	On the challenges of detecting MCI using EEG in the wild. CoRR Aayush Mishra, David Joffe, Sankara Surendra Telidevara, David S. Oakley, Anqi Liu
2025	—	`conf`	Privacy Preserving Ordinal-Meta Learning with VLMs for Fine-Grained Fruit Quality Prediction. CVPR Workshops Riddhi Jain, Manasi Patwardhan, Aayush Mishra, Parijat Deshpande, Beena Rai
2025	J	`jnl`	Privacy Preserving Ordinal-Meta Learning with VLMs for Fine-Grained Fruit Quality Prediction. CoRR Riddhi Jain, Manasi Patwardhan, Aayush Mishra, Parijat Deshpande, Beena Rai
2025	J	`jnl`	Robust Amortized Bayesian Inference with Self-Consistency Losses on Unlabeled Data. CoRR Aayush Mishra, Daniel Habermann, Marvin Schmitt, Stefan T. Radev, Paul-Christian Bürkner
2025	J	`jnl`	Towards Trustworthy Amortized Bayesian Model Comparison. CoRR Simon Kucharský, Aayush Mishra, Daniel Habermann, Stefan T. Radev, Paul-Christian Bürkner
2024	—	`conf`	Ordinal-Meta Learning for Fine-Grained Fruit Quality Prediction. ECCV Workshops (3) Aayush Mishra, Manasi Patwardhan, Parijat Deshpande, Beena Rai
2024	A*	`conf`	Position: Do pretrained Transformers Learn In-Context by Gradient Descent? ICML Lingfeng Shen, Aayush Mishra, Daniel Khashabi
2024	A*	`conf`	Source-Free and Image-Only Unsupervised Domain Adaptation for Category Level Object Pose Estimation. ICLR Prakhar Kaushik, Aayush Mishra, Adam Kortylewski, Alan L. Yuille
2024	J	`jnl`	Source-Free and Image-Only Unsupervised Domain Adaptation for Category Level Object Pose Estimation. CoRR Prakhar Kaushik, Aayush Mishra, Adam Kortylewski, Alan L. Yuille
2023	J	`jnl`	DECODE: Data-driven Energy Consumption Prediction leveraging Historical Data and Environmental Factors in Buildings. CoRR Aditya Mishra, Haroon R. Lone, Aayush Mishra
2023	J	`jnl`	Do pretrained Transformers Really Learn In-context by Gradient Descent? CoRR Lingfeng Shen, Aayush Mishra, Daniel Khashabi
2023	J	`jnl`	Stress Testing Chain-of-Thought Prompting for Large Language Models. CoRR Aayush Mishra, Karan Thakkar
2022	J	`jnl`	Repeated Environment Inference for Invariant Learning. CoRR Aayush Mishra, Anqi Liu
2019	A	`conf`	VStegNET: Video Steganography Network using Spatio-Temporal features and Micro-Bottleneck. BMVC Aayush Mishra, Suraj Kumar, Aditya Nigam, Saiful Islam