Publications

Bayesian Adaptation Gym: A Benchmark for the Bayesian Low-Rank Adaptation of Multi-Modal Language Models

Colin Samplawski, Ramneet Kaur, Manoj Acharya, Anirban Roy, Adam D. Cobb

Amsterdam, Netherlands

Formally Verified Code Synthesis for Structured Data Translation in a Medical Internet of Things

Colin Samplawski, Adam D. Cobb

International Conference on Machine Learning ICML

Seoul, South Korea

“Do Diffusion Models Dream of Electric Planes?” Discrete and Continuous Simulation-Based Inference for Aircraft Design

Aurelien Ghiglino, Daniel Elenius, Anirban Roy, Ramneet Kaur, Manoj Acharya, Colin Samplawski, Brian Matejek, Susmit Jha, Juan Alonso, Adam D. Cobb

Seoul, South Korea

Generating Vehicle Designs Using Probabilistic Programs and Reinforcement Learning

Daniel Elenius, Aurelien Ghiglino, Krishiv Agarwal, Colin Samplawski, Anirban Roy, Susmit Jha, Juan Jose Alonso, Adam D. Cobb

Cavtat, Croatia

Privacy Preserving In-Context-Learning Framework for Large Language Models

Bishnu Bhusal, Manoj Acharya, Ramneet Kaur, Colin Samplawski, Anirban Roy, Adam D. Cobb, Rohit Chadha, Susmit Jha

Singapore

Breaking Bad: Interpretability-Based Safety Audits of State-of-the-Art LLMs

Krishiv Agarwal, Ramneet Kaur, Colin Samplawski, Manoj Acharya, Anirban Roy, Daniel Elenius, Brian Matejek, Adam D. Cobb, Susmit Jha

Conference on Neural Information Processing Systems NeurIPS

San Diego, CA

A Preliminary Study into the Conceptual Design of Aircraft using Simulation-Based Inference

Aurelien Ghiglino, Daniel Elenius, Anirban Roy, Ramneet Kaur, Manoj Acharya, Colin Samplawski, Brian Matejek, Susmit Jha, Juan Alonso, Adam Cobb

Conference on Neural Information Processing Systems NeurIPS

San Diego, CA

Scalable Bayesian Low-Rank Adaptation of Large Language Models via Stochastic Variational Subspace Inference

Colin Samplawski, Adam D. Cobb, Manoj Acharya, Ramneet Kaur, Susmit Jha

Rio de Janeiro, Brazil

End-to-End Differentiable Multi-View Tracking: Architecture and Fine-Tuning Experiments

Colin Samplawski, Shiwei Fang, Benjamin M. Marlin

Rio de Janeiro, Brazil

AGENT: An Aerial Vehicle Generation and Design Tool Using Large Language Models

Colin Samplawski, Adam D. Cobb, Susmit Jha

Addressing Uncertainty in LLMs to Enhance Reliability in Generative AI

Ramneet Kaur, Colin Samplawski, Adam D. Cobb, Anirban Roy, Brian Matejek, Manoj Acharya, Daniel Elenius, Alexander Michael Berenbeim, John A. Pavlik, Nathaniel D. Bastian, Susmit Jha

Conference on Neural Information Processing Systems NeurIPS

Vancouver, Canada

FlexLoc: Conditional Neural Networks for Zero-Shot Sensor Perspective Invariance in Object Localization with Distributed Multimodal Sensors

Jason Wu, Ziqi Wang, Xiaomin Ouyang, Ho Lyun Jeong, Colin Samplawski, Lance M. Kaplan, Benjamin Marlin, Mani Srivastava

Abu Dhabi, UAE

Temporally Multi-Scale Sparse Self-Attention for Physical Activity Data Imputation

Hui Wei, Maxwell A. Xu, Colin Samplawski, James M. Rehg, Santosh Kumar, Benjamin M. Marlin

New York, NY

IoBT-MAX: A Multimodal Analytics eXperimentation Testbed for IoBT Research

Benjamin M. Marlin, Niranjan Suri, Shiwei Fang, Mani B. Srivastava, Colin Samplawski, Ziqi Wang, Maggie Wigness

Boston, MA

Heteroskedastic Geospatial Tracking with Distributed Camera Networks

Colin Samplawski, Shiwei Fang, Ziqi Wang, Deepak Ganesan, Mani Srivastava, Benjamin M. Marlin

Pittsburgh, PA

Uncertainty Quantification Using Query-Based Object Detectors

Meet P. Vadera, Colin Samplawski, Benjamin M. Marlin

17th European Conference on Computer Vision ECCV

Tel Aviv, Israel

Optimizing Intelligent Edge-clouds with Partitioning, Compression and Speculative Inference

Shiwei Fang, Jin Huang, Colin Samplawski, Deepak Ganesan, Benjamin Marlin, Tarek Abdelzaher, Maggie B. Wigness

San Diego, CA

Towards Transformer-Based Real-Time Object Detection at the Edge: A Benchmarking Study

Colin Samplawski, Benjamin M. Marlin

San Diego, CA

Towards an Accurate Latency Model for Convolutional Neural Network Layers on GPUs

Jinyang Li, Runyu Ma, Vikram Sharma Mailthody, Colin Samplawski, Benjamin Marlin, Songqing Chen, Shuochao Yao, Tarek Abdelzaher

San Diego, CA

Towards Object Detection Under IoT Resource Constraints: Combining Partitioning, Slicing and Compression

Colin Samplawski, Jin Huang, Deepak Ganesan, Benjamin M. Marlin

18th ACM Conference on Embedded Networked Sensor Systems SenSys

Virtual

CLIO: Enabling Automatic Compilation of Deep Learning Pipelines Across IoT and Cloud

Jin Huang, Colin Samplawski, Deepak Ganesan, Benjamin M. Marlin, Heesung Kwon

London, United Kingdom

Zero-Shot Learning in the Presence of Hierarchically Coarsened Labels

Colin Samplawski, Erik Learned-Miller, Heesung Kwon, Benjamin M. Marlin

IEEE/CVF Conference on Computer Vision and Pattern Recognition CVPR

Virtual

Learning Graph-Based Priors for Generalized Zero-Shot Learning

Colin Samplawski, Jannik Wolff, Tassilo Klein, Moin Nabi

34th AAAI Conference on Artificial Intelligence AAAI

New York, NY

Weakly Supervised Content and Style Disentanglement with Gaussian Mixture VAEs

Jan Nikolas Morshuis, Colin Samplawski, Moin Nabi

Conference on Neural Information Processing Systems NeurIPS

Vancouver, Canada