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07/13/2023
Domain-Agnostic Tuning-Encoder for Fast Personalization of Text-To-Image Models
Text-to-image (T2I) personalization allows users to guide the creative i...
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06/18/2023
Point-Cloud Completion with Pretrained Text-to-image Diffusion Models
Point-cloud data collected in real-world applications are often incomple...
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06/15/2023
Linguistic Binding in Diffusion Models: Enhancing Attribute Correspondence through Attention Map Alignment
Text-conditioned image generation models often generate incorrect associ...
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05/30/2023
DisCLIP: Open-Vocabulary Referring Expression Generation
Referring Expressions Generation (REG) aims to produce textual descripti...
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05/02/2023
Key-Locked Rank One Editing for Text-to-Image Personalization
Text-to-image models (T2I) offer a new level of flexibility by allowing ...
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05/02/2023
CALM: Conditional Adversarial Latent Models for Directable Virtual Characters
In this work, we present Conditional Adversarial Latent Models (CALM), a...
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03/06/2023
Graph Positional Encoding via Random Feature Propagation
Two main families of node feature augmentation schemes have been explore...
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02/23/2023
Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Models
Text-to-image personalization aims to teach a pre-trained diffusion mode...
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02/19/2023
Guided Deep Kernel Learning
Combining Gaussian processes with the expressive power of deep neural ne...
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01/31/2023
Auxiliary Learning as an Asymmetric Bargaining Game
Auxiliary learning is an effective method for enhancing the generalizati...
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01/30/2023
SoftTreeMax: Exponential Variance Reduction in Policy Gradient via Tree Search
Despite the popularity of policy gradient methods, they are known to suf...
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01/30/2023
Equivariant Architectures for Learning in Deep Weight Spaces
Designing machine learning architectures for processing neural networks ...
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01/26/2023
Train Hard, Fight Easy: Robust Meta Reinforcement Learning
A major challenge of reinforcement learning (RL) in real-world applicati...
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10/27/2022
Text2Model: Model Induction for Zero-shot Generalization Using Task Descriptions
We study the problem of generating a training-free task-dependent visual...
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09/28/2022
SoftTreeMax: Policy Gradient with Tree Search
Policy-gradient methods are widely used for learning control policies. T...
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08/02/2022
An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion
Text-to-image models offer unprecedented freedom to guide creation throu...
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07/05/2022
Implementing Reinforcement Learning Datacenter Congestion Control in NVIDIA NICs
Cloud datacenters are exponentially growing both in numbers and size. Th...
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05/30/2022
Reinforcement Learning with a Terminator
We present the problem of reinforcement learning with exogenous terminat...
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04/18/2022
Optimizing Tensor Network Contraction Using Reinforcement Learning
Quantum Computing (QC) stands to revolutionize computing, but is current...
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04/04/2022
"This is my unicorn, Fluffy": Personalizing frozen vision-language representations
Large Vision Language models pretrained on web-scale data provide re...
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03/27/2022
Example-based Hypernetworks for Out-of-Distribution Generalization
While Natural Language Processing (NLP) algorithms keep reaching unprece...
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02/02/2022
Learning to reason about and to act on physical cascading events
Reasoning and interacting with dynamic environments is a fundamental pro...
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02/02/2022
Multi-Task Learning as a Bargaining Game
In Multi-task learning (MTL), a joint model is trained to simultaneously...
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01/28/2022
Planning and Learning with Adaptive Lookahead
The classical Policy Iteration (PI) algorithm alternates between greedy ...
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01/20/2022
Federated Learning with Heterogeneous Architectures using Graph HyperNetworks
Standard Federated Learning (FL) techniques are limited to clients with ...
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11/16/2021
Inference-Time Personalized Federated Learning
In Federated learning (FL), multiple clients collaborate to learn a mode...
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10/13/2021
Object-Region Video Transformers
Evidence from cognitive psychology suggests that understanding spatio-te...
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10/13/2021
On Covariate Shift of Latent Confounders in Imitation and Reinforcement Learning
We consider the problem of using expert data with unobserved confounders...
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08/02/2021
StyleGAN-NADA: CLIP-Guided Domain Adaptation of Image Generators
Can a generative model be trained to produce images from a specific doma...
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07/04/2021
Improve Agents without Retraining: Parallel Tree Search with Off-Policy Correction
Tree Search (TS) is crucial to some of the most influential successes in...
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06/29/2021
Personalized Federated Learning with Gaussian Processes
Federated learning aims to learn a global model that performs well on cl...
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06/08/2021
DETReg: Unsupervised Pretraining with Region Priors for Object Detection
Unsupervised pretraining has recently proven beneficial for computer vis...
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04/07/2021
Distributional Robustness Loss for Long-tail Learning
Real-world data is often unbalanced and long-tailed, but deep models str...
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03/08/2021
Personalized Federated Learning using Hypernetworks
Personalized federated learning is tasked with training machine learning...
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02/18/2021
Reinforcement Learning for Datacenter Congestion Control
We approach the task of network congestion control in datacenters using ...
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02/15/2021
GP-Tree: A Gaussian Process Classifier for Few-Shot Incremental Learning
Gaussian processes (GPs) are non-parametric, flexible, models that work ...
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01/26/2021
Automatic Curation of Large-Scale Datasets for Audio-Visual Representation Learning
Large-scale datasets are the cornerstone of self-supervised representati...
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10/20/2020
Teacher-Student Consistency For Multi-Source Domain Adaptation
In Multi-Source Domain Adaptation (MSDA), models are trained on samples ...
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10/17/2020
On Size Generalization in Graph Neural Networks
Graph neural networks (GNNs) can process graphs of different sizes but t...
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10/11/2020
How to Stop Epidemics: Controlling Graph Dynamics with Reinforcement Learning and Graph Neural Networks
We consider the problem of monitoring and controlling a partially-observ...
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10/08/2020
Learning the Pareto Front with Hypernetworks
Multi-objective optimization problems are prevalent in machine learning....
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10/07/2020
ZEST: Zero-shot Learning from Text Descriptions using Textual Similarity and Visual Summarization
We study the problem of recognizing visual entities from the textual des...
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09/30/2020
Learning Object Detection from Captions via Textual Scene Attributes
Object detection is a fundamental task in computer vision, requiring lar...
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06/27/2020
Compositional Video Synthesis with Action Graphs
Videos of actions are complex spatio-temporal signals, containing rich c...
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06/25/2020
A causal view of compositional zero-shot recognition
People easily recognize new visual categories that are new combinations ...
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06/17/2020
Contrastive Learning for Weakly Supervised Phrase Grounding
Phrase grounding, the problem of associating image regions to caption wo...
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04/05/2020
Long-tail learning with attributes
Learning to classify images with unbalanced class distributions is chall...
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03/29/2020
Self-Supervised Learning for Domain Adaptation on Point-Clouds
Self-supervised learning (SSL) allows to learn useful representations fr...
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03/23/2020
Learning Object Permanence from Video
Object Permanence allows people to reason about the location of non-visi...
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02/20/2020