Colin Samplawski

26 papers A* 2A 3C 1Journal 12Unranked 8

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Do Diffusion Models Dream of Electric Planes? Discrete and Continuous Simulation-Based Inference for Aircraft Design. CoRR Aurelien Ghiglino, Daniel Elenius, Anirban Roy, Ramneet Kaur, Manoj Acharya, Colin Samplawski, Brian Matejek, Susmit Jha, Juan Alonso, Adam D. Cobb
2026	A*	`conf`	Privacy Preserving In-Context-Learning Framework for Large Language Models. AAAI Bishnu Bhusal, Manoj Acharya, Ramneet Kaur, Colin Samplawski, Anirban Roy, Adam D. Cobb, Rohit Chadha, Susmit Jha
2025	J	`jnl`	AGENT: An Aerial Vehicle Generation and Design Tool Using Large Language Models. CoRR Colin Samplawski, Adam D. Cobb, Susmit Jha
2025	J	`jnl`	Calibrating Uncertainty Quantification of Multi-Modal LLMs using Grounding. CoRR Trilok Padhi, Ramneet Kaur, Adam D. Cobb, Manoj Acharya, Anirban Roy, Colin Samplawski, Brian Matejek, Alexander M. Berenbeim, Nathaniel D. Bastian, Susmit Jha
2025	C	`conf`	End-to-End Differentiable Multi-View Tracking: Architecture and Fine-Tuning Experiments. FUSION Colin Samplawski, Shiwei Fang, Benjamin M. Marlin
2025	J	`jnl`	Privacy-Aware In-Context Learning for Large Language Models. CoRR Bishnu Bhusal, Manoj Acharya, Ramneet Kaur, Colin Samplawski, Anirban Roy, Adam D. Cobb, Rohit Chadha, Susmit Jha
2025	A	`conf`	Scalable Bayesian Low-Rank Adaptation of Large Language Models via Stochastic Variational Subspace Inference. UAI Colin Samplawski, Adam D. Cobb, Manoj Acharya, Ramneet Kaur, Susmit Jha
2025	J	`jnl`	Scalable Bayesian Low-Rank Adaptation of Large Language Models via Stochastic Variational Subspace Inference. CoRR Colin Samplawski, Adam D. Cobb, Manoj Acharya, Ramneet Kaur, Susmit Jha
2024	J	`jnl`	Addressing Uncertainty in LLMs to Enhance Reliability in Generative AI. CoRR Ramneet Kaur, Colin Samplawski, Adam D. Cobb, Anirban Roy, Brian Matejek, Manoj Acharya, Daniel Elenius, Alexander M. Berenbeim, John A. Pavlik, Nathaniel D. Bastian, Susmit Jha
2024	A	`conf`	FlexLoc: Conditional Neural Networks for Zero-Shot Sensor Perspective Invariance in Object Localization with Distributed Multimodal Sensors. IROS Jason Wu, Ziqi Wang, Xiaomin Ouyang, Ho Lyun Jeong, Colin Samplawski, Lance M. Kaplan, Benjamin M. Marlin, Mani Srivastava
2024	J	`jnl`	FlexLoc: Conditional Neural Networks for Zero-Shot Sensor Perspective Invariance in Object Localization with Distributed Multimodal Sensors. CoRR Jason Wu, Ziqi Wang, Xiaomin Ouyang, Ho Lyun Jeong, Colin Samplawski, Lance M. Kaplan, Benjamin M. Marlin, Mani Srivastava
2024	J	`jnl`	GDTM: An Indoor Geospatial Tracking Dataset with Distributed Multimodal Sensors. CoRR Ho Lyun Jeong, Ziqi Wang, Colin Samplawski, Jason Wu, Shiwei Fang, Lance M. Kaplan, Deepak Ganesan, Benjamin M. Marlin, Mani Srivastava
2024	—	`conf`	Temporally Multi-Scale Sparse Self-Attention for Physical Activity Data Imputation. CHIL Hui Wei, Maxwell A. Xu, Colin Samplawski, James Matthew Rehg, Santosh Kumar, Benjamin M. Marlin
2024	J	`jnl`	Temporally Multi-Scale Sparse Self-Attention for Physical Activity Data Imputation. CoRR Hui Wei, Maxwell A. Xu, Colin Samplawski, James M. Rehg, Santosh Kumar, Benjamin M. Marlin
2023	A	`conf`	Heteroskedastic Geospatial Tracking with Distributed Camera Networks. UAI Colin Samplawski, Shiwei Fang, Ziqi Wang, Deepak Ganesan, Mani B. Srivastava, Benjamin M. Marlin
2023	J	`jnl`	Heteroskedastic Geospatial Tracking with Distributed Camera Networks. CoRR Colin Samplawski, Shiwei Fang, Ziqi Wang, Deepak Ganesan, Mani B. Srivastava, Benjamin M. Marlin
2023	—	`conf`	IoBT-MAX: a Multimodal Analytics eXperimentation Testbed for IoBT Research. MILCOM Benjamin M. Marlin, Niranjan Suri, Shiwei Fang, Mani B. Srivastava, Colin Samplawski, Ziqi Wang, Maggie B. Wigness
2022	—	`conf`	Uncertainty Quantification Using Query-Based Object Detectors. ECCV Workshops (8) Meet P. Vadera, Colin Samplawski, Benjamin M. Marlin
2021	—	`conf`	Optimizing Intelligent Edge-clouds with Partitioning, Compression and Speculative Inference. MILCOM Shiwei Fang, Jin Huang, Colin Samplawski, Deepak Ganesan, Benjamin M. Marlin, Tarek F. Abdelzaher, Maggie B. Wigness
2021	—	`conf`	Towards Transformer-Based Real-Time Object Detection at the Edge: A Benchmarking Study. MILCOM Colin Samplawski, Benjamin M. Marlin
2021	—	`conf`	Towards an Accurate Latency Model for Convolutional Neural Network Layers on GPUs. MILCOM Jinyang Li, Runyu Ma, Vikram Sharma Mailthody, Colin Samplawski, Benjamin M. Marlin, Songqing Chen, Shuochao Yao, Tarek F. Abdelzaher
2020	A*	`conf`	CLIO: enabling automatic compilation of deep learning pipelines across IoT and cloud. MobiCom Jin Huang, Colin Samplawski, Deepak Ganesan, Benjamin M. Marlin, Heesung Kwon
2020	J	`jnl`	Learning Graph-Based Priors for Generalized Zero-Shot Learning. CoRR Colin Samplawski, Jannik Wolff, Tassilo Klein, Moin Nabi
2020	—	`conf`	Towards Objection Detection Under IoT Resource Constraints: Combining Partitioning, Slicing and Compression. AIChallengeIoT@SenSys Colin Samplawski, Jin Huang, Deepak Ganesan, Benjamin M. Marlin
2020	—	`conf`	Zero-Shot Learning in the Presence of Hierarchically Coarsened Labels. CVPR Workshops Colin Samplawski, Erik G. Learned-Miller, Heesung Kwon, Benjamin M. Marlin
2019	J	`jnl`	Integrating Propositional and Relational Label Side Information for Hierarchical Zero-Shot Image Classification. CoRR Colin Samplawski, Heesung Kwon, Erik G. Learned-Miller, Benjamin M. Marlin