| Title | Students |
|---|---|
| Transformer based multi-task learning for predicting student coding performance | Sai Vineeth Kalluru Srinivas, Yijing Bai |
| Exploring the Role of Novel Class Detection in Few-shot Detection | Xinran Zhao, Xiaoyuan Ni |
| Representation Search in Neural Space for Image Compression | ZhuoYi Cai |
| Improving Few-Shot Learning Performance by Fine-Tuning Late Layers | Wenxin Dong, Kevin Lit |
| Few Shot Learning with a FiLM-Generator Network | Ethan Cheng |
| Few-shot Multimodal Multitask Multilingual Learning | Aman Chadha |
| Meta-Learning for Better Learning: Automatically Tagging Learning Goals | Amir Zur |
| Emotion-Cause Pair Extraction with Hybrid Architecture Analysis | Ta-Hsuan Chao, Yi-Chia Wu, Pei-Wei Kao |
| Looking Big-Picture: Leveraging a Few Demos to Learn from Unlabeled Play Data | Maximilian Du |
| Improving Sub-group Robustness for EEG Seizure Detection | Yixing Jiang |
| Online Meta-learning for time series data | Aman Bansal, Pranay Reddy Samala, Shubham Anand Jain |
| Domain- Aware Mental Health Virtual Assistant | Yunan Li, Heidi Zhang, Lynette Gao |
| Meta Learning for Few-Shot Object Detection | Shunyao Xu, Zhiling Huang, Shenghan Chen |
| Few-shot classification of drug target activity augmented with pretrained protein embeddings | David Huang, Tom Pritsky, David Kuo |
| DABS: JAX MAE Implementation & Cross-Domain Transfer Learning | Eden Y Wang |
| Implict MAML based SDFs | Samaksh Goyal |
| Model Fine-tuning Layer Prediction for Surgical Fine-tuning Tasks | Angela Liu |
| Multitask learning from egocentric infant headcam data | Alvin Wei Ming Tan |
| Prediction of Rare Metastatic Cancer from RNA Data in Few-Shot Settings | Mohammad (Jabs) Aljubran, Alaskar Alizada |
| Diffusion Models as Visual Reasoners | Maya Sharanya Srikanth, Jason Jiachen Lin |
| Can Systematic Manipulation of Compositional Shared Substructure of Tasks Change the "Difficulty" of a Meta-Learning task? | Mohammad Ali Rehan, Pratyush Agarwal, Saumya Goyal |
| Synthetic Data Generation for Few-Shot Learning | Ofure Mary Ebhomielen, Vaish Shrivastava, Rajan Pathe Vivek |
| Conservative Out-of-Distribution Detection | Caroline Choi |
| Solving the Camouflage Object Segmentation Problem with Multitask-Learning and MAML Augmented SINet | Xin Zhang, William L Cai |
| Task Fusion: Specializing Common Representations in Multi-Task Learning | Dennis J Duan, Ayush Singla, Ananth Agarwal |
| Global Health Monitoring From Satellite Data Through Multi-Task Learning | Sharmila Nangi, Nick Tantivasadakarn |
| Garbage Classification Using Multi Task Learning | Goutham Krishna Teja Muppala |
| Generating Adversarial Meta-Learning Tasks via Noise Memorization | Daniel David Richman, Shai Limonchik |
| Using Safe RL to Generalize the Minimum Spanning Tree Problem | Anthony Tzen, Jensen Hwa, Ali Teshnizi |
| Bringing Multitask Learning in identifying the existence of Social Determinant of Health in Clinical Reports | Ranajit Gangopadhyay |
| Layer Autotuning: Automated Fine-tuning Algorithms For Transfer Learning | Shaunak Bhandarkar, Kai Mica Fronsdal, Kelechi Uhegbu |
| Application and Study of Meta Learning on Land Cover Classification and Crop Prediction | Chuanqi Chen, Hongxu Ma, Chung Ching Cheung |
| Meta-learning approaches to bird species classification | Justine Breuch, Cameron David Tew, Miles Richard Hutson |
| Quantifying Diversity of Large Language Model Pretraining Datasets for Studying Emergence of In-Context Learning | Alycia Lee |
| History-Aware Perceiver-Actor For Multi-Task Robot Manipulation | Ziang Liu, Blair Huang |
| Essays: New Approaches to Multi-task and Transfer Learning for Long SequenceTexts and Complex Inter-task Relationships | Michael Hardy |
| Improving Blood Glucose Prediction Using Meta Learning | Akshat Nath Mishra |
| Few-Shot Handwritten Chinese Character Classification | Eric Chen |
| Application of Prototypical networks with Few-Shot Learning for Art Analysis and Classification | Lara Malinov |
| Urban Land Cover for Water Conservation and Management | Brandon Wada |
| Meta-Learning to Mitigate Noise Propagation in Gradual Self-Training | Angela Tsao |
| Mapping Visual Features to Differences in Operative Skill, Intraoperative Events, and Post-Operative Outcomes for Laparoscopic Cholecystectomy | Shelly Goel |
| Automatic fine-tuning | Nipun Agarwala, Neal Rakesh Vaidya, Haider Suleman |
| Distribute Hierarchical Meta Reinforce Learners | Mustafa Bayramov |
| Building a Robust Rare Activities Detection System with Limited Data | Natasha Ong, Mac Klinkachorn, Jeffrey Halim |
| Coefficient Based Fine-tuning of Language Models on Distribution Shifts | Suma Kasa, Antoine Bigeard, Samuel Barry |
| Learning to Augment | Chang Li, Mingshan Wang, Wen Xu |
| TimeGraphs: Meta-Learning over Time using Graph Neural Networks | Paridhi Maheshwari |
| MAMLSS: Extending Self-Supervision to Model Agnostic Meta-learning | Ishira U Fernando, Michael Jonathan Atkin |
| Conditioning Generative Language Models for Finetunability | Matt Smith |
| Prototypes, Contrastive Learning And Classification Under Novelty | Advaya Gupta, Jinang Rupeshkumar Shah, Aditya Ashwini Agrawal |
| Adapting Large Language Models to Solve Word Puzzles with Shared Intermediate Steps | Jing Huang |
| Learning Virtual Machine Duration for Resource Allocation in the Cloud Computing Environment | Madhumita Vijay Dange, Yuwen Yang |
| Image Compression using Implicit Neural Representation | Huafan Cai |
| Does surgical fine-tuning work in NLP and does it reflect the classical N L P pipeline? | Pooja Sethi |
| Specializing Common Representations in Multi-Task Learning | Tom Keohane Murray, Silviu Ionut Lazar, Luke Hein Martin |
| Meta-learning for digital audio effects | Lucy Lu, Dirk Stallard Roosenburg, Ivan Villa-Renteria |
| Increased Concept Diversity Improves In-Context Learning on Unseen Concepts | Haishan Gao |
| Analyzing latent representations in trained MAMLs | Ryan Lian, Sri Jaladi, Victor Stilianov Kolev |
| Gradient-Based Meta Learning for Morphologically Diverse Few-Shot Cell Segmentation | Rohan Sikand |
| Surgical Fine-tuning, Automated Surgical Fine-tuning Metrics | Muhammad Ghazi Randhawa |
| Studying the Robustness of Transformer-based Imitation Learning to Domain Shift | Nick Soulounias, Sidhart Krishnan, Avidesh F Marajh |
| Bias Transfer from Source Datasets when Fine-tuning | Nicole Meister |
| Instance Specific Data Augmentation for meta-learning | Pranay Agrawal, Eric Tang |
| Using Multiple Task and Meta-Learning Networks for Board-Based Game Strategy Development | Ian Yue Han Ng, Brian Y Wu, Benjamin Bin Yan |
| Meta-Learning Optimal Simulator Fidelity Settings For Autonomous System Validation | Marc Schlichting |
| Offline Meta-Reinforcement Learning: Extending MACAW | Daniel Havir |
| PIGEON: Predicting Image Geolocations | Michal Skreta, Lukas Haas, Silas Alberti |
| Semi Supervised Meta Learning for Spatiotemporal Learning | Pratyush Muthukumar, Faraz Waseem, Muhammad Shahir Rahman |
| Meta-Learning to Locally Predict Free-Flight Potential | Drew Wadsworth |
| Studying the Robustness of Transformer-based Imitation Learning to Domain Shift | Axel Peytavin, Leqi Zeng, Matthew Thomas |
| TLDChoiceNet: Quantitatively Choosing a Transfer Learning Dataset | James Duncan Braza, Anna NING |
| Convex prototypical networks with ReLU activation | Devin Ardeshna |
| Meta Learning on Comments for Code Comprehension | Aditya Chandrasekar |
| A cost efficient scalable method to extend to low-resource languages for ASR models | Yuxin Ding |
| Learning Protein Functional Annotation from Few-Shot Data via Meta-Learning | Aditya Gulati, Keerti Kareti |
| Multimodal Self-Pretraining for Medical Image Classification | Cara Elise Van Uden, Gordon Downs, Ben Alexander |
| Meta-Learning for Electronic Health Records | Rishi Agarwal, Tathagat Verma |
| Parameter Level Surgical Fine-Tuning for Transformers | Siyan Sylvia Li, Kathy Yu |
| MLETA: Meta Learning for Efficient Test-time Adaptation | Ansh Khurana, Soumya Chatterjee, Aman Kansal |
| Self-Driving Web Browsers | Bryan Chiang |
| Meta-learning for multi-horizon limit order book return prediction | Charles Congyue Chen |
| 3KG v2: Learning universal electrocardiogram representations for label-efficient phenotype discovery | Bryan Dev Gopal |
| Instance-Specific Augmenter Using Representation Matching | Rajas Bansal, Atharva Amdekar, Anuj Nagpal |
| Meta-Learning Independent Representations for Counterfactual Time Series Generation | Sven Lerner, Greg Zanotti |
| Class imbalance in meta-test support sets | Ajay Kannan |
| Augmentation by Distillation | Sanjit Neelam |
| Few-shot QA tasks | Adil Sadik |
| Gradient-Informed Branching For Multi-Task Learning | Gautam Mittal, Leni Ven, Zedian Xiao |
| Meta-GAT: Few Shot Node Classification with Graph Attention Networks | Nabil Ahmed |
| Automatic Selective Layer-Wise Task-Specific Fine-Tuning Improves Transfer Learning | Chunming Peng, Matt Peng, Rongbin Li |
| Domain Adaptive Learning on Brain Networks | David Dai |
| Expert Affinity Grouping for Multi-Task Learning | Peter Michael Paquet |
| Categorized and Self-diagnose Neural Network approach for Continual learning | Rong Chen |
| MetaAugNet: Learning Data Augmentations on the Fly | Alex Zachary Fan, Brian Wesley Hill, Yoko Nagafuchi |
| Single Life Reinforcement Learning with Quadruped Robots | Govind Chada |
| Enriching Model Representation With Adaptive Modulated Learning | Yibo Zhang |
| Apply Task-adaptive Inner-loop Loss Tuning in MAML | Jiwen Chen |
| Meta-Learning Force Fields | David J Toomer |
| Few-Shot Speaker Identification Using Masked Autoencoders and Meta-Learning | John Boccio |
| Wormhole MAML: Meta-Learning In Glued Parameter Space | Yuan Gao, Beicheng Lou, Tracy Chang |
| Assessing Meta-Reinforcement Learning Algorithms in Complex Environments | Michael Hany Elabd, Ronak Anuj Malde |
| How Does Parameter Sharing Affect Multi-task Learning? | Tz-Wei Mo, Annie Ho, Li-Heng Lin |
| Towards More Robust Natural Language Prompting for Multi-Task Text Classification | Violet Yao, Chenshu Zhu, Shirley Shuocheng Zhang |
| Enriching Model Representation With Adaptive Modulated Features For Multitask Learning | Xinglong Sun, Yibo Zhang |
| Evaluating several methods for mixing knowledge of Vietnamese and knowledge of law | Pham Thanh Huu |
| Self-Supervised learning for identifying fishes | Aleksandr Timashov |
| Adapting to Unknown Conventions in Cooperative Multi-Agent RL | Bidipta Sarkar |
| Semi-Supervised Learning of Multi-Task Contrast-Weighted Image Synthesis from Magnetic Resonance Fingerprinting | Phil Michael Adamson, Mahmut Yurt |
| Fine-tuning a visual transformer for PV detection in varying resolutions | Rajanie Prabha, Ivan Gonzalo Higuera-Mendieta |
| Investigating Optimal AMA Prompting Strategies for Small Foundation Models | Andrew Louis Hojel, Oscar O'Rahilly, Aayush Amit Agrawal |
| SayAgain: Prompt-tuning for improved planning with large language models | Michael John Lingelbach, Gabrael Levine |
| Unsupervised Real2Sim Transfer for Safe Evaluation of Autonomous Vehicles | Anirudhan Badrinath |
| SOAR: Single-Shot Multi-Task Object Action Recognition | Tiange Xiang, Zhuoyi Huang |
| Transfer-Learning and Fine-Tuning across Time-Series Spectrogram Tasks | Xiang Jiang, Michael Gregory Campiglia, Ryan Tan |
| Transfer and Meta-Learning in Graph Neural Networks: A Recommender System Approach | Megan Backus, Hamdy Hamoudi, Rouven Spiess |
| Exploring transferability and model agnostic meta learning across NLP Tasks | Phillip Yao-Lakaschus, Marcos Silveira, Karen Garcia Mesa |
| Contrastive and Adversarial Learning for Few-shot Image Classification | Gary Dai, Joanne Zhou |
| User Rating Prediction and Product Recommendation on Amazon Reviews | Jordan Patrick Byrd, Li Tian, Sylvia Yuan |
| AHA-Ensemble: Automatic Heterogeneous Architecture Ensembles for Domain Generalization | Javier Yu |
| Controlling Catastrophic Forgetting Using Feature-based Knowledge Distillation | Ali H Shoeb |
| How to Preserve Adversarial Robustness During Transfer Learning | Laura Fee Schneider, Maurice Andre Georgi |
| Few-Shot 3D Object Detection | Kutluhan Buvukburc |