Devin T. WILLMOTT

ELICITING BLACK-BOX REPRESENTATIONS FROM MACHINE LEARNING MODELS THROUGH SELF-QUERIES

MIMETIC INITIALIZATION OF SELF-ATTENTION LAYERS

SYSTEM AND METHOD FOR HIGH-RESOLUTION BLACKBOX PATCH ATTACK WITH BAYESIAN OPTMIZIATION

SYSTEM AND METHOD FOR QUERY EFFICIENT BLACKBOX PHYSICALLY REALIZABLE ATTACK WITH BAYESIAN OPTIMIZATION

SYSTEM AND METHOD FOR FINUTING OF ZERO-SHOT VISION MODELS

MULTIVARIATE INITIALIZATION FOR CONVOLUTIONAL LAYERS

FEDERATED LEARNING WITH FOUNDATION MODEL DISTILLATION

FEDERATED LEARNING WITH FOUNDATION MODEL DISTILLATION

SYSTEM AND METHOD FOR PROMPT SEARCHING

SYSTEM AND METHOD FOR LEVARGING MULTIPLE DESCRIPTIVE FEATURES FOR ROBUST FEW-SHOT IMAGE LEARNING

METHODS AND SYSTEMS FOR PERFORMING ROOT CAUSE ANALYSIS WITH A TRAINED MACHINE LEARNING MODEL

METHODS AND SYSTEMS FOR TRAINING A MACHINE LEARNING MODEL WITH MEASUREMENT DATA CAPTURED DURING MANUFACTURING PROCESS

Data augmentation for domain generalization

DEEP EQUILIBRIUM FLOW ESTIMATION

NEURAL DEEP EQUILIBRIUM SOLVER

MONOTONE MEAN-FIELD INFERENCE IN DEEP MARKOV RANDOM FIELDS

Image processing via isotonic convolutional neural networks

EQUILIBRIUM MODELS ACCELERATION VIA JACOBIANS STABILIZATION SYSTEMS AND METHODS

Image segmention via efficient semidefinate-programming based inference for binary and multi-class Markov Random Fields

Method and system for low-query black-box universal attacks

System and method for multiscale deep equilibrium models

Meta-learned, evolution strategy black box optimization classifiers