Nilesh A. Ahuja

42 papers A* 2A 1B 5Journal 26Unranked 8

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	ContraGS: Codebook-Condensed and Trainable Gaussian Splatting for Fast, Memory-Efficient Reconstruction. CoRR Sankeerth Durvasula, Sharanshangar Muhunthan, Zain Moustafa, Richard Chen, Ruofan Liang, Yushi Guan, Nilesh A. Ahuja, Nilesh Jain, Selvakumar Panneer, Nandita Vijaykumar
2025	—	`conf`	INRet: A General Framework for Accurate Retrieval of INRs for Shapes. 3DV Yushi Guan, Daniel Kwan, Ruofan Liang, Selvakumar Panneer, Nilesh Jain, Nilesh A. Ahuja, Nandita Vijaykumar
2025	J	`jnl`	INRet: A General Framework for Accurate Retrieval of INRs for Shapes. CoRR Yushi Guan, Daniel Kwan, Ruofan Liang, Selvakumar Panneer, Nilesh Jain, Nilesh A. Ahuja, Nandita Vijaykumar
2025	J	`jnl`	MoRA: Missing Modality Low-Rank Adaptation for Visual Recognition. CoRR Shu Zhao, Nilesh A. Ahuja, Tan Yu, Tianyi Shen, Vijaykrishnan Narayanan
2025	J	`jnl`	Rate-Distortion Theory in Coding for Machines and Its Applications. IEEE Trans. Pattern Anal. Mach. Intell. Alon Harell, Yalda Foroutan, Nilesh A. Ahuja, Parual Datta, Bhavya Kanzariya, V. Srinivasa Somayazulu, Omesh Tickoo, Anderson de Andrade, Ivan V. Bajic
2025	A*	`conf`	Retri3D: 3D Neural Graphics Representation Retrieval. ICLR Yushi Guan, Daniel Kwan, Jean Sebastien Dandurand, Xi Yan, Ruofan Liang, Yuxuan Zhang, Nilesh Jain, Nilesh A. Ahuja, Selvakumar Panneer, Nandita Vijaykumar
2025	J	`jnl`	TS-OOD: Evaluating Time-Series Out-of-Distribution Detection and Prospective Directions for Progress. CoRR Onat Güngör, Amanda Sofie Rios, Nilesh A. Ahuja, Tajana Rosing
2025	J	`jnl`	Windsock is Dancing: Adaptive Multimodal Retrieval-Augmented Generation. CoRR Shu Zhao, Tianyi Shen, Nilesh A. Ahuja, Omesh Tickoo, Vijaykrishnan Narayanan
2024	—	`conf`	A Robust Framework for Evaluation of Unsupervised Time-Series Anomaly Detection. ICPR (26) Onat Güngör, Amanda Rios, Priyanka Mudgal, Nilesh A. Ahuja, Tajana Rosing
2024	J	`jnl`	CONCLAD: COntinuous Novel CLAss Detector. CoRR Amanda Rios, Ibrahima J. Ndiour, Parual Datta, Omesh Tickoo, Nilesh A. Ahuja
2024	J	`jnl`	CUAL: Continual Uncertainty-aware Active Learner. CoRR Amanda Rios, Ibrahima J. Ndiour, Parual Datta, Jerry Sydir, Omesh Tickoo, Nilesh A. Ahuja
2024	—	`conf`	Compression without Compromise: Optimizing Point Cloud Object Detection with Bottleneck Architectures For Split Computing. ICME Workshops Vinay Kashyap, Nilesh A. Ahuja, Omesh Tickoo
2024	—	`conf`	Split-DNN Computing for Video Analytics. ICPR (3) Nagabhushan Eswara, Jaroslaw Sydir, V. Srinivasa Somayazulu, Parual Datta, Nilesh A. Ahuja, Omesh Tickoo
2024	J	`jnl`	Uncertainty Quantification in Continual Open-World Learning. CoRR Amanda Sofie Rios, Ibrahima J. Ndiour, Parual Datta, Jaroslaw Sydir, Omesh Tickoo, Nilesh A. Ahuja
2023	A	`conf`	FRE: A Fast Method For Anomaly Detection And Segmentation. BMVC Ibrahima J. Ndiour, Nilesh A. Ahuja, Ergin Utku Genc, Omesh Tickoo
2023	A*	`conf`	Neural Rate Estimator and Unsupervised Learning for Efficient Distributed Image Analytics in Split-DNN models. CVPR Nilesh A. Ahuja, Parual Datta, Bhavya Kanzariya, V. Srinivasa Somayazulu, Omesh Tickoo
2023	J	`jnl`	Rate-Distortion Theory in Coding for Machines and its Application. CoRR Alon Harell, Yalda Foroutan, Nilesh A. Ahuja, Parual Datta, Bhavya Kanzariya, V. Srinivasa Somayazulu, Omesh Tickoo, Anderson de Andrade, Ivan V. Bajic
2022	B	`conf`	A Low-Complexity Approach to Rate-Distortion Optimized Variable Bit-Rate Compression for Split DNN Computing. ICPR Parual Datta, Nilesh A. Ahuja, V. Srinivasa Somayazulu, Omesh Tickoo
2022	J	`jnl`	A Low-Complexity Approach to Rate-Distortion Optimized Variable Bit-Rate Compression for Split DNN Computing. CoRR Parual Datta, Nilesh A. Ahuja, V. Srinivasa Somayazulu, Omesh Tickoo
2022	B	`conf`	Anomalib: A Deep Learning Library for Anomaly Detection. ICIP Samet Akcay, Dick Ameln, Ashwin Vaidya, Barath Lakshmanan, Nilesh A. Ahuja, Ergin Utku Genc
2022	J	`jnl`	Anomalib: A Deep Learning Library for Anomaly Detection. CoRR Samet Akcay, Dick Ameln, Ashwin Vaidya, Barath Lakshmanan, Nilesh A. Ahuja, Ergin Utku Genc
2022	—	`conf`	Continual Active Adaptation to Evolving Distributional Shifts. CVPR Workshops Amrutha Machireddy, Ranganath Krishnan, Nilesh A. Ahuja, Omesh Tickoo
2022	J	`jnl`	End-to-End Industrial IoT: Software Optimization and Acceleration. IEEE Internet Things Mag. Meena Arunachalam, Vrushabh Sanghavi, Samudyatha Kaira, Nilesh A. Ahuja
2022	J	`jnl`	FRE: A Fast Method For Anomaly Detection And Segmentation. CoRR Ibrahima J. Ndiour, Nilesh A. Ahuja, Ergin Utku Genc, Omesh Tickoo
2022	B	`conf`	Subspace Modeling for Fast Out-Of-Distribution and Anomaly Detection. ICIP Ibrahima J. Ndiour, Nilesh A. Ahuja, Omesh Tickoo
2022	J	`jnl`	Subspace Modeling for Fast Out-Of-Distribution and Anomaly Detection. CoRR Ibrahima J. Ndiour, Nilesh A. Ahuja, Omesh Tickoo
2022	—	`conf`	incDFM: Incremental Deep Feature Modeling for Continual Novelty Detection. ECCV (25) Amanda Rios, Nilesh A. Ahuja, Ibrahima J. Ndiour, Ergin Utku Genc, Laurent Itti, Omesh Tickoo
2021	—	`conf`	E2E Visual Analytics: Achieving >10X Edge/Cloud Optimizations. NAS Chaunte Lacewell, Nilesh A. Ahuja, J. Pablo Munoz, Parual Datta, Ragaad AlTarawneh, Vui Seng Chua, Nilesh Jain, Omesh Tickoo, Ravi Iyer
2021	J	`jnl`	Energy-Based Anomaly Detection and Localization. CoRR Ergin Utku Genc, Nilesh A. Ahuja, Ibrahima J. Ndiour, Omesh Tickoo
2021	J	`jnl`	Improving Robustness and Efficiency in Active Learning with Contrastive Loss. CoRR Ranganath Krishnan, Nilesh A. Ahuja, Alok Sinha, Mahesh Subedar, Omesh Tickoo, Ravi Iyer
2021	J	`jnl`	Mitigating Sampling Bias and Improving Robustness in Active Learning. CoRR Ranganath Krishnan, Alok Sinha, Nilesh A. Ahuja, Mahesh Subedar, Omesh Tickoo, Ravi Iyer
2020	J	`jnl`	Out-Of-Distribution Detection With Subspace Techniques And Probabilistic Modeling Of Features. CoRR Ibrahima J. Ndiour, Nilesh A. Ahuja, Omesh Tickoo
2020	B	`conf`	Semantic-Preserving Image Compression. ICIP Neel Patwa, Nilesh A. Ahuja, V. Srinivasa Somayazulu, Omesh Tickoo, Srenivas Varadarajan, Shashidhar G. Koolagudi
2019	J	`jnl`	Deep Probabilistic Models to Detect Data Poisoning Attacks. CoRR Mahesh Subedar, Nilesh A. Ahuja, Ranganath Krishnan, Ibrahima J. Ndiour, Omesh Tickoo
2019	J	`jnl`	Probabilistic Modeling of Deep Features for Out-of-Distribution and Adversarial Detection. CoRR Nilesh A. Ahuja, Ibrahima J. Ndiour, Trushant Kalyanpur, Omesh Tickoo
2019	J	`jnl`	Real-time Approximate Bayesian Computation for Scene Understanding. CoRR Javier Felip, Nilesh A. Ahuja, David Gómez-Gutiérrez, Omesh Tickoo, Vikash Mansinghka
2019	J	`jnl`	Tree pyramidal adaptive importance sampling. CoRR Javier Felip, Nilesh A. Ahuja, Omesh Tickoo
2017	—	`conf`	A Factorization Approach for Enabling Structure-from-Motion/SLAM Using Integer Arithmetic. ICCV Workshops Nilesh A. Ahuja, Mahesh Subedar, Omesh Tickoo, Yeongseon Lee
2007	J	`jnl`	Design of Large Field-of-View High-Resolution Miniaturized Imaging System. EURASIP J. Adv. Signal Process. Nilesh A. Ahuja, Nirmal K. Bose
2006	B	`conf`	Multidimensional Generalized Sampling Theorem for wavelet Based Image Superresolution. ICIP Nilesh A. Ahuja, Nirmal K. Bose
2006	J	`jnl`	Superresolution and noise filtering using moving least squares. IEEE Trans. Image Process. Nirmal K. Bose, Nilesh A. Ahuja
2005	J	`jnl`	Spatiotemporal-bandwidth product of m-dimensional signals. IEEE Signal Process. Lett. Nilesh A. Ahuja, Nirmal K. Bose