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09/19/2023
Guide Your Agent with Adaptive Multimodal Rewards
Developing an agent capable of adapting to unseen environments remains a...
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08/15/2023
NeFL: Nested Federated Learning for Heterogeneous Clients
Federated learning (FL) is a promising approach in distributed learning ...
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07/12/2023
Towards Safe Self-Distillation of Internet-Scale Text-to-Image Diffusion Models
Large-scale image generation models, with impressive quality made possib...
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05/31/2023
Accelerating Reinforcement Learning with Value-Conditional State Entropy Exploration
A promising technique for exploration is to maximize the entropy of visi...
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03/25/2023
IFSeg: Image-free Semantic Segmentation via Vision-Language Model
Vision-language (VL) pre-training has recently gained much attention for...
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03/24/2023
Enhancing Multiple Reliability Measures via Nuisance-extended Information Bottleneck
In practical scenarios where training data is limited, many predictive s...
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03/20/2023
Imitating Graph-Based Planning with Goal-Conditioned Policies
Recently, graph-based planning algorithms have gained much attention to ...
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03/06/2023
Guiding Energy-based Models via Contrastive Latent Variables
An energy-based model (EBM) is a popular generative framework that offer...
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03/02/2023
Unsupervised Meta-Learning via Few-shot Pseudo-supervised Contrastive Learning
Unsupervised meta-learning aims to learn generalizable knowledge across ...
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03/02/2023
Preference Transformer: Modeling Human Preferences using Transformers for RL
Preference-based reinforcement learning (RL) provides a framework to tra...
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02/15/2023
Video Probabilistic Diffusion Models in Projected Latent Space
Despite the remarkable progress in deep generative models, synthesizing ...
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02/05/2023
Multi-View Masked World Models for Visual Robotic Manipulation
Visual robotic manipulation research and applications often use multiple...
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02/01/2023
Efficient Meta-Learning via Error-based Context Pruning for Implicit Neural Representations
We introduce an efficient optimization-based meta-learning technique for...
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01/23/2023
Modality-Agnostic Variational Compression of Implicit Neural Representations
We introduce a modality-agnostic neural data compression algorithm based...
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12/18/2022
Confidence-aware Training of Smoothed Classifiers for Certified Robustness
Any classifier can be "smoothed out" under Gaussian noise to build a new...
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12/13/2022
OAMixer: Object-aware Mixing Layer for Vision Transformers
Patch-based models, e.g., Vision Transformers (ViTs) and Mixers, have sh...
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12/05/2022
Breaking the Spurious Causality of Conditional Generation via Fairness Intervention with Corrective Sampling
Trying to capture the sample-label relationship, conditional generative ...
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10/13/2022
Scalable Neural Video Representations with Learnable Positional Features
Succinct representation of complex signals using coordinate-based neural...
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10/11/2022
Meta-Learning with Self-Improving Momentum Target
The idea of using a separately trained target model (or teacher) to impr...
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08/23/2022
String-based Molecule Generation via Multi-decoder VAE
In this paper, we investigate the problem of string-based molecular gene...
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08/10/2022
Robust Continual Test-time Adaptation: Instance-aware BN and Prediction-balanced Memory
Test-time adaptation (TTA) is an emerging paradigm that addresses distri...
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07/19/2022
Time Is MattEr: Temporal Self-supervision for Video Transformers
Understanding temporal dynamics of video is an essential aspect of learn...
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06/16/2022
Patch-level Representation Learning for Self-supervised Vision Transformers
Recent self-supervised learning (SSL) methods have shown impressive resu...
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04/05/2022
Zero-shot Blind Image Denoising via Implicit Neural Representations
Recent denoising algorithms based on the "blind-spot" strategy show impr...
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04/05/2022
Spread Spurious Attribute: Improving Worst-group Accuracy with Spurious Attribute Estimation
The paradigm of worst-group loss minimization has shown its promise in a...
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03/18/2022
SURF: Semi-supervised Reward Learning with Data Augmentation for Feedback-efficient Preference-based Reinforcement Learning
Preference-based reinforcement learning (RL) has shown potential for tea...
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02/21/2022
Generating Videos with Dynamics-aware Implicit Generative Adversarial Networks
In the deep learning era, long video generation of high-quality still re...
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12/16/2021
Saliency Grafting: Innocuous Attribution-Guided Mixup with Calibrated Label Mixing
The Mixup scheme suggests mixing a pair of samples to create an augmente...
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11/22/2021
DAPPER: Performance Estimation of Domain Adaptation in Mobile Sensing
Many applications that utilize sensors in mobile devices and apply machi...
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11/18/2021
Improving Transferability of Representations via Augmentation-Aware Self-Supervision
Recent unsupervised representation learning methods have shown to be eff...
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11/17/2021
SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness
Randomized smoothing is currently a state-of-the-art method to construct...
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10/27/2021
Meta-Learning Sparse Implicit Neural Representations
Implicit neural representations are a promising new avenue of representi...
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10/27/2021
RoMA: Robust Model Adaptation for Offline Model-based Optimization
We consider the problem of searching an input maximizing a black-box obj...
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10/27/2021
Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning
Behavioral cloning has proven to be effective for learning sequential de...
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10/26/2021
Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning
Goal-conditioned hierarchical reinforcement learning (HRL) has shown pro...
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07/30/2021
Object-aware Contrastive Learning for Debiased Scene Representation
Contrastive self-supervised learning has shown impressive results in lea...
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07/22/2021
Abstract Reasoning via Logic-guided Generation
Abstract reasoning, i.e., inferring complicated patterns from given obse...
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07/01/2021
Offline-to-Online Reinforcement Learning via Balanced Replay and Pessimistic Q-Ensemble
Recent advance in deep offline reinforcement learning (RL) has made it p...
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06/28/2021
Co^2L: Contrastive Continual Learning
Recent breakthroughs in self-supervised learning show that such algorith...
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06/15/2021
Scaling Neural Tangent Kernels via Sketching and Random Features
The Neural Tangent Kernel (NTK) characterizes the behavior of infinitely...
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06/09/2021
Self-Improved Retrosynthetic Planning
Retrosynthetic planning is a fundamental problem in chemistry for findin...
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05/03/2021
RetCL: A Selection-based Approach for Retrosynthesis via Contrastive Learning
Retrosynthesis, of which the goal is to find a set of reactants for synt...
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05/03/2021
Consistency and Monotonicity Regularization for Neural Knowledge Tracing
Knowledge Tracing (KT), tracking a human's knowledge acquisition, is a c...
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04/03/2021
Random Features for the Neural Tangent Kernel
The Neural Tangent Kernel (NTK) has discovered connections between deep ...
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03/17/2021
Training GANs with Stronger Augmentations via Contrastive Discriminator
Recent works in Generative Adversarial Networks (GANs) are actively revi...
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03/08/2021
Consistency Regularization for Adversarial Robustness
Adversarial training (AT) is currently one of the most successful method...
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02/18/2021
State Entropy Maximization with Random Encoders for Efficient Exploration
Recent exploration methods have proven to be a recipe for improving samp...
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02/07/2021
Model-Augmented Q-learning
In recent years, Q-learning has become indispensable for model-free rein...
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12/17/2020
MASKER: Masked Keyword Regularization for Reliable Text Classification
Pre-trained language models have achieved state-of-the-art accuracies on...
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10/26/2020