conftrace_

gradient flow

142 papers

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Also known as

GF

Co-occurring keywords

neural network (6616) gradient descent (1144) optimal transport (948) implicit bia (107) relu network (143) neural network optimization (1293) stochastic gradient descent (1091) convergence analysis (395) variational inference (2069) wasserstein distance (417)

Papers

Unpacking the Implicit Norm Dynamics of Sharpness-Aware Minimization in Tensorized Models AAAI 2026
Stabilizing Direct Training of Spiking Neural Networks: Membrane Potential Initialization and Threshold-robust Surrogate Gradient WACV 2026
Effects of Momentum in Implicit Bias of Gradient Flow for Diagonal Linear Networks AAAI 2025
(De)-regularized Maximum Mean Discrepancy Gradient Flow JMLR 2025
FreEformer: Frequency Enhanced Transformer for Multivariate Time Series Forecasting IJCAI 2025
Towards Understanding Gradient Flow Dynamics of Homogeneous Neural Networks Beyond the Origin JMLR 2025
SGDPO: Self-Guided Direct Preference Optimization for Language Model Alignment ACL 2025
Error bounds for particle gradient descent, and extensions of the log-Sobolev and Talagrand inequalities JMLR 2025
Symbolic Neural Ordinary Differential Equations AAAI 2025
Towards Better Spherical Sliced-Wasserstein Distance Learning with Data-Adaptive Discriminative Projection Direction AAAI 2025
Trained Transformers Learn Linear Models In-Context JMLR 2024
Learnability of high-dimensional targets by two-parameter models and gradient flow NIPS 2024
Interaction-Force Transport Gradient Flows NIPS 2024
Separation and Bias of Deep Equilibrium Models on Expressivity and Learning Dynamics NIPS 2024
On the Impact of Overparameterization on the Training of a Shallow Neural Network in High Dimensions AISTATS 2024
Training Dynamics of Multi-Head Softmax Attention for In-Context Learning: Emergence, Convergence, and Optimality (extended abstract) COLT 2024
Training Dynamics of Transformers to Recognize Word Co-occurrence via Gradient Flow Analysis NIPS 2024
Deep linear networks for regression are implicitly regularized towards flat minima NIPS 2024
Lexicographic Optimization: Algorithms and Stability AISTATS 2024
Improving Adaptivity via Over-Parameterization in Sequence Models NIPS 2024
A Comparison of Continuous-Time Approximations to Stochastic Gradient Descent JMLR 2024
Minimizing Convex Functionals over Space of Probability Measures via KL Divergence Gradient Flow AISTATS 2024
Global Convergence in Training Large-Scale Transformers NIPS 2024
Topological obstruction to the training of shallow ReLU neural networks NIPS 2024
Functional Gradient Flows for Constrained Sampling NIPS 2024