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08/01/2023
Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models
Today, large language models (LLMs) are taught to use new tools by provi...
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06/15/2023
Re-Benchmarking Pool-Based Active Learning for Binary Classification
Active learning is a paradigm that significantly enhances the performanc...
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05/03/2023
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes
Deploying large language models (LLMs) is challenging because they are m...
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03/10/2023
TSMixer: An all-MLP Architecture for Time Series Forecasting
Real-world time-series datasets are often multivariate with complex dyna...
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02/06/2023
Pic2Word: Mapping Pictures to Words for Zero-shot Composed Image Retrieval
In Composed Image Retrieval (CIR), a user combines a query image with te...
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11/30/2022
SPADE: Semi-supervised Anomaly Detection under Distribution Mismatch
Semi-supervised anomaly detection is a common problem, as often the data...
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06/02/2022
Prefix Conditioning Unifies Language and Label Supervision
Vision-language contrastive learning suggests a new learning paradigm by...
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03/30/2022
Learning Instance-Specific Adaptation for Cross-Domain Segmentation
We propose a test-time adaptation method for cross-domain image segmenta...
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03/16/2022
FormNet: Structural Encoding beyond Sequential Modeling in Form Document Information Extraction
Sequence modeling has demonstrated state-of-the-art performance on natur...
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02/04/2022
Decoupling Local and Global Representations of Time Series
Real-world time series data are often generated from several sources of ...
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12/21/2021
Anomaly Clustering: Grouping Images into Coherent Clusters of Anomaly Types
We introduce anomaly clustering, whose goal is to group data into semant...
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11/03/2021
Improving Model Compatibility of Generative Adversarial Networks by Boundary Calibration
Generative Adversarial Networks (GANs) is a powerful family of models th...
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11/01/2021
A Unified View of cGANs with and without Classifiers
Conditional Generative Adversarial Networks (cGANs) are implicit generat...
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10/27/2021
Robust Contrastive Learning Using Negative Samples with Diminished Semantics
Unsupervised learning has recently made exceptional progress because of ...
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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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06/21/2021
ROPE: Reading Order Equivariant Positional Encoding for Graph-based Document Information Extraction
Natural reading orders of words are crucial for information extraction f...
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06/11/2021
Self-Trained One-class Classification for Unsupervised Anomaly Detection
Anomaly detection (AD), separating anomalies from normal data, has vario...
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05/31/2021
DISSECT: Disentangled Simultaneous Explanations via Concept Traversals
Explaining deep learning model inferences is a promising venue for scien...
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04/08/2021
CutPaste: Self-Supervised Learning for Anomaly Detection and Localization
We aim at constructing a high performance model for defect detection tha...
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11/04/2020
Learning and Evaluating Representations for Deep One-class Classification
We present a two-stage framework for deep one-class classification. We f...
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10/19/2020
PseudoSeg: Designing Pseudo Labels for Semantic Segmentation
Recent advances in semi-supervised learning (SSL) demonstrate that a com...
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10/17/2020
i-Mix: A Strategy for Regularizing Contrastive Representation Learning
Contrastive representation learning has shown to be an effective way of ...
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08/03/2020
Interpretable Sequence Learning for COVID-19 Forecasting
We propose a novel approach that integrates machine learning into compar...
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07/06/2020
Kernel Stein Generative Modeling
We are interested in gradient-based Explicit Generative Modeling where s...
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05/10/2020
A Simple Semi-Supervised Learning Framework for Object Detection
Semi-supervised learning (SSL) has promising potential for improving the...
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01/27/2020
Unsupervised Program Synthesis for Images using Tree-Structured LSTM
Program synthesis has recently emerged as a promising approach to the im...
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01/21/2020
FixMatch: Simplifying Semi-Supervised Learning with Consistency and Confidence
Semi-supervised learning (SSL) provides an effective means of leveraging...
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12/08/2019
Learned Interpolation for 3D Generation
In order to generate novel 3D shapes with machine learning, one must all...
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12/08/2019
Getting Topology and Point Cloud Generation to Mesh
In this work, we explore the idea that effective generative models for p...
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10/17/2019
On Concept-Based Explanations in Deep Neural Networks
Deep neural networks (DNNs) build high-level intelligence on low-level r...
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08/20/2019
Developing Creative AI to Generate Sculptural Objects
We explore the intersection of human and machine creativity by generatin...
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04/22/2019
LBS Autoencoder: Self-supervised Fitting of Articulated Meshes to Point Clouds
We present LBS-AE; a self-supervised autoencoding algorithm for fitting ...
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02/26/2019
Implicit Kernel Learning
Kernels are powerful and versatile tools in machine learning and statist...
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01/18/2019
Kernel Change-point Detection with Auxiliary Deep Generative Models
Detecting the emergence of abrupt property changes in time series is a c...
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11/13/2018
Hallucinating Point Cloud into 3D Sculptural Object
Our team of artists and machine learning researchers designed a creative...
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10/13/2018
Point Cloud GAN
Generative Adversarial Networks (GAN) can achieve promising performance ...
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08/08/2018
Adversarial Geometry and Lighting using a Differentiable Renderer
Many machine learning classifiers are vulnerable to adversarial attacks,...
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08/08/2018
Beyond Pixel Norm-Balls: Parametric Adversaries using an Analytically Differentiable Renderer
Many machine learning image classifiers are vulnerable to adversarial at...
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05/22/2018
Nonparametric Density Estimation under Adversarial Losses
We study minimax convergence rates of nonparametric density estimation u...
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04/05/2018
Pedestrian-Synthesis-GAN: Generating Pedestrian Data in Real Scene and Beyond
State-of-the-art pedestrian detection models have achieved great success...
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11/14/2017
Sobolev GAN
We propose a new Integral Probability Metric (IPM) between distributions...
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05/24/2017
MMD GAN: Towards Deeper Understanding of Moment Matching Network
Generative moment matching network (GMMN) is a deep generative model tha...
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05/23/2017
Data-driven Random Fourier Features using Stein Effect
Large-scale kernel approximation is an important problem in machine lear...
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03/29/2017
One Network to Solve Them All --- Solving Linear Inverse Problems using Deep Projection Models
While deep learning methods have achieved state-of-the-art performance i...
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11/11/2016
Annealing Gaussian into ReLU: a New Sampling Strategy for Leaky-ReLU RBM
Restricted Boltzmann Machine (RBM) is a bipartite graphical model that i...
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06/04/2015