yusuke1997/dblp-id-title huggingface dataset:
Understanding Counterfactual Generation using Maximum Mean Discrepancy
Risk and return prediction for pricing portfolios of non-performing consumer credit
Analysis of the impact of maker-taker fees on the stock market using agent-based simulation
AI versus AI in Financial Crimes & Detection: GenAI Crime Waves to Co-Evolutionary AI
Deep risk model: a deep learning solution for mining latent risk factors to improve covariance matrix estimation
Towards self-regulating AI: challenges and opportunities of AI model governance in financial services
An Interpretable Deep Classifier for Counterfactual Generation
FraudGT: A Simple, Effective, and Efficient Graph Transformer for Financial Fraud Detection
Financial network games
Can GANs Learn the Stylized Facts of Financial Time Series?
Functional Mixed-type Clustering of Investors' Daily Returns During a Market Shock Change-point and Recovery
Simulating the Economic Impact of Rationality through Reinforcement Learning and Agent-Based Modelling
Optimal, truthful, and private securities lending
Improving the Robustness of Financial Models through Identification of the Minimal Vulnerable Feature Set
Stability effects of arbitrage in exchange traded funds: an agent-based model
RESHAPE: Explaining Accounting Anomalies in Financial Statement Audits by enhancing SHapley Additive exPlanations
Co-Training Realized Volatility Prediction Model with Neural Distributional Transformation
The Network of Mutual Funds: A Dynamic Heterogeneous Graph Neural Network for Estimating Mutual Funds Performance
Monte carlo tree search for trading and hedging
On Correlated Stock Market Time Series Generation
Dynamic prediction length for time series with sequence to sequence network
Asynchronous collaborative learning across data silos
Recommending missing and suspicious links in multiplex financial networks
FinQAPT: Empowering Financial Decisions with End-to-End LLM-driven Question Answering Pipeline
To Compete or Collude: Bidding Incentives in Ethereum Block Building Auctions
LaundroGraph: Self-Supervised Graph Representation Learning for Anti-Money Laundering
Deep Learning for Options Trading: An End-To-End Approach
Contrastive Learning of Asset Embeddings from Financial Time Series
Multi-Modal Financial Time-Series Retrieval Through Latent Space Projections
RiskMiner: Discovering Formulaic Alphas via Risk Seeking Monte Carlo Tree Search
Subgraph anomaly detection in financial transaction networks
4th ACM International Conference on AI in Finance, ICAIF 2023, Brooklyn, NY, USA, November 27-29, 2023
An analysis of political turmoil effects on stock prices: a case study of US-China trade friction
Margin Trader: A Reinforcement Learning Framework for Portfolio Management with Margin and Constraints
Lifting Volterra Diffusions via Kernel Decomposition
A strategic analysis of portfolio compression
Turbo-Charging Deep Learning Methods for Partial Differential Equations
Profit equitably: an investigation of market maker's impact on equitable outcomes
Quantifying Outlierness of Funds from their Categories using Supervised Similarity
FinRL-podracer: high performance and scalable deep reinforcement learning for quantitative finance
Tradeoffs in streaming binary classification under limited inspection resources
Asset Price and Direction Prediction via Deep 2D Transformer and Convolutional Neural Networks
NMTucker: Non-linear Matryoshka Tucker Decomposition for Financial Time Series Imputation
Addressing Extreme Market Responses Using Secure Aggregation
Augmenting Equity Factor Investing with Global Macro Regimes
Timing is money: the impact of arrival order in beta-bernoulli prediction markets
Reinforcement Learning for Intra-and-Inter-Bank Borrowing and Lending Mean Field Control Game
Fund2Vec: mutual funds similarity using graph learning
Market Making with Scaled Beta Policies
Quantum Generative Models of Mid-Price Movement in Limit Order Books
Deep reinforcement learning for automated stock trading: an ensemble strategy
Power-law mixtures of bayesian forests for value added tax audit case selection
HybridRAG: Integrating Knowledge Graphs and Vector Retrieval Augmented Generation for Efficient Information Extraction
A machine learning approach to detect early signs of startup success
Deep Q-network-based adaptive alert threshold selection policy for payment fraud systems in retail banking
Enhancing Financial Sentiment Analysis via Retrieval Augmented Large Language Models
Graph Denoising Networks: A Deep Learning Framework for Equity Portfolio Construction
Online Personalizing White-box LLMs Generation with Neural Bandits
Time horizon-aware modeling of financial texts for stock price prediction
Trading via image classification
Stable Multilevel Deep Neural Networks for Option Pricing and xVAs Using Forward-Backward Stochastic Differential Equations
The complexity of financial wellness: examining survey patterns via kernel metric learning and clustering of mixed-type data
AuthSHAP: authentication vulnerability detection on tabular data in black box setting
E2EAI: End-to-End Deep Learning Framework for Active Investing
Navigating the Difficulty of Achieving Global Optimality under Variance-Induced Time Inconsistency
Temporal Bipartite Graph Neural Networks for Bond Prediction
TADACap: Time-series Adaptive Domain-Aware Captioning
Making LLMs Worth Every Penny: Resource-Limited Text Classification in Banking
Numin: Weighted-Majority Ensembles for Intraday Trading
Adversarial Inverse Reinforcement Learning for Market Making
Objective Driven Portfolio Construction Using Reinforcement Learning
Unsupervised-learning financial reconciliation: a robust, accurate approach inspired by machine translation
Equity2Vec: end-to-end deep learning framework for cross-sectional asset pricing
Reinforcement Learning for Combining Search Methods in the Calibration of Economic ABMs
Neural Term Structure of Additive Process for Option Pricing
Cryptocurrency volatility forecasting using commonality in intraday volatility
Algorithms in future capital markets: a survey on AI, ML and associated algorithms in capital markets
Federated and Privacy-Preserving Learning of Accounting Data in Financial Statement Audits
Intelligent Inventory Management for Cryptocurrency Brokers
Monotonic Neural Additive Models: Pursuing Regulated Machine Learning Models for Credit Scoring
Intelligent trading systems: a sentiment-aware reinforcement learning approach
Learning knowledge-enriched company embeddings for investment management
Evaluating Financial Relational Graphs: Interpretation Before Prediction
Cluster-driven Hierarchical Representation of Large Asset Universes for Optimal Portfolio Construction
Predictability of Post-Earnings Announcement Drift with Textual and Contextual Factors of Earnings Calls
High frequency automated market making algorithms with adverse selection risk control via reinforcement learning
Mixtures of Experts for Scaling up Neural Networks in Order Execution
Simulate and Optimise: A two-layer mortgage simulator for designing novel mortgage assistance products
Navigating the dynamics of financial embeddings over time
Fast Deep Hedging with Second-Order Optimization
ICAIF '20: The First ACM International Conference on AI in Finance, New York, NY, USA, October 15-16, 2020
FinDiff: Diffusion Models for Financial Tabular Data Generation
Foreign exchange trading: a risk-averse batch reinforcement learning approach
NFT Primary Sale Price and Secondary Sale Prediction via Deep Learning
A hybrid learning approach to detecting regime switches in financial markets
Addressing Non-Stationarity in FX Trading with Online Model Selection of Offline RL Experts
CaPE: Category Preserving Embeddings for Similarity-Search in Financial Graphs
Bankruptcy Prediction: Data Augmentation, LLMs and the Need for Auditor's Opinion
Order Flow Decomposition for Price Impact Analysis in Equity Limit Order Books
Data-driven Derivative Hedging with Quadratic Variation Penalty
The evolving causal structure of equity risk factors
Adversarial Fraud Generation for Improved Detection
Classifying high-frequency FX rate movements with technical indicators and inception model
LLMs Analyzing the Analysts: Do BERT and GPT Extract More Value from Financial Analyst Reports?
Sequential Fair Resource Allocation under a Markov Decision Process Framework
Sig-wasserstein GANs for time series generation
Financial misstatement detection: a realistic evaluation
SimStock : Representation Model for Stock Similarities
A Case Study on Enhancing Inquiry Response in a Non-Life Insurance Company Using Generative AI
Tab-Distillation: Impacts of Dataset Distillation on Tabular Data For Outlier Detection
The efficient hedging frontier with deep neural networks
Graph and tensor-train recurrent neural networks for high-dimensional models of limit order books
The Effect of Liquidity on the Spoofability of Financial Markets
Explainable clustering and application to wealth management compliance
Simulating and classifying behavior in adversarial environments based on action-state traces: an application to money laundering
Fine-Tuning Pretrained Language Models to Enhance Dialogue Summarization in Customer Service Centers
A tabular sarsa-based stock market agent
Simulating Asset Prices using Conditional Time-Series GAN
Modeling Inverse Demand Function with Explainable Dual Neural Networks
On the current and emerging challenges of developing fair and ethical AI solutions in financial services
A Financial Time Series Denoiser Based on Diffusion Models
Deep Calibration of Market Simulations using Neural Density Estimators and Embedding Networks
From Pixels to Predictions: Spectrogram and Vision Transformer for Better Time Series Forecasting
The Default Cascade Process in Stochastic Financial Networks
AI in Investment Analysis: LLMs for Equity Stock Ratings
Reducing Return Volatility in Neural Network-Based Asset Allocation via Formal Verification and Certified Training
Network Filtering of Spatial-temporal GNN for Multivariate Time-series Prediction
Transforming Unstructured Sensitive Information into Structured Knowledge
Retrieval Augmented Fraud Detection
Imb-FinDiff: Conditional Diffusion Models for Class Imbalance Synthesis of Financial Tabular Data
Learning to simulate realistic limit order book markets from data as a World Agent
Dynamic Reinforced Ensemble using Bayesian Optimization for Stock Trading
Efficient Event Series Data Modeling via First-Order Constrained Optimization
Mechanistic interpretability of large language models with applications to the financial services industry
Evaluating Fairness in Transaction Fraud Models: Fairness Metrics, Bias Audits, and Challenges
Sig-SDEs model for quantitative finance
Deep video prediction for time series forecasting
Decentralization Analysis of Pooling Behavior in Cardano Proof of Stake
Liquidity and Solvency Risks in Financial Networks
Financial table extraction in image documents
Deep Q-learning market makers in a multi-agent simulated stock market
Can an unsupervised clustering algorithm reproduce a categorization system?
Trading via selective classification
Graphical models for financial time series and portfolio selection
Towards a Foundation Purchasing Model: Pretrained Generative Autoregression on Transaction Sequences
Learning regulator influence on internal risk weights
Lending an Ear: How LLMs Hear Your Banking Intentions
SigFormer: Signature Transformers for Deep Hedging
Get real: realism metrics for robust limit order book market simulations
Choosing news topics to explain stock market returns
JAX-LOB: A GPU-Accelerated limit order book simulator to unlock large scale reinforcement learning for trading
Active learning for imbalanced data under cold start
Extracting Alpha from Financial Analyst Networks
Understanding distributional ambiguity via non-robust chance constraint
Learning Temporal Representations of Bipartite Financial Graphs
Multi-view contrastive self-supervised learning of accounting data representations for downstream audit tasks
Market-Making and Hedging with Market Impact using Deep Reinforcement Learning
StyleTime: Style Transfer for Synthetic Time Series Generation
Customized FinGPT Search Agents Using Foundation Models
Large Scale Financial Time Series Forecasting with Multi-faceted Model
LLMs for Financial Advisement: A Fairness and Efficacy Study in Personal Decision Making
Conditional Generators for Limit Order Book Environments: Explainability, Challenges, and Robustness
Transformers and attention-based networks in quantitative trading: a comprehensive survey
Optimal Stopping with Gaussian Processes
A Machine Learning Plus-Features Based Approach for Optimal Asset Allocation
Utilization of deep learning to mine insights from earning calls for stock price movement predictions
What can be learned from satisfaction assessments?
Detecting Collective Liquidity Taking Distributions
Dyn-GWN: Time-Series Forecasting using Time-varying Graphs with Applications to Finance and Traffic Prediction
Achieving Mean-Variance Efficiency by Continuous-Time Reinforcement Learning
Why Groups Matter: Necessity of Group Structures in Attributions
Adaptive and Explainable Margin Trading via Large Language Models on Portfolio Management
Guided Self-Training based Semi-Supervised Learning for Fraud Detection
Designing Expressive and Liquid Financial Options Markets via Linear Programming and Automated Market Making
Dynamic Time Warping for Lead-Lag Relationship Detection in Lagged Multi-Factor Models
Enhanced Local Explainability and Trust Scores with Random Forest Proximities
Gradient-Assisted Calibration for Financial Agent-Based Models
Market Making under Order Stacking Framework: A Deep Reinforcement Learning Approach
Earnings Call Analysis Using a Sparse Attention Based Encoder and Multi-Source Counterfactual Augmentation
Generative Machine Learning for Multivariate Equity Returns
Tax Credits and Household Behavior: The Roles of Myopic Decision-Making and Liquidity in a Simulated Economy
Social media data reveals signal for public consumer perceptions
ML-Assisted Optimization of Securities Lending
Learning sampling in financial statement audits using vector quantised variational autoencoder neural networks
Adversarial Deep Hedging: Learning to Hedge without Price Process Modeling
From Detection to Action: a Human-in-the-loop Toolkit for Anomaly Reasoning and Management
A Deep Learning Approach for Dynamic Balance Sheet Stress Testing
Predicting the behavior of dealers in over-the-counter corporate bond markets
Towards realistic market simulations: a generative adversarial networks approach
Learning to Manipulate a Financial Benchmark
Generative AI for End-to-End Limit Order Book Modelling: A Token-Level Autoregressive Generative Model of Message Flow Using a Deep State Space Network
Modality-aware Transformer for Financial Time series Forecasting
Sequential asset ranking in nonstationary time series
Incentivising Market Making in Financial Markets
Generative-CNN for Pattern Recognition in Finance
DySTAGE: Dynamic Graph Representation Learning for Asset Pricing via Spatio-Temporal Attention and Graph Encodings
SecretMatch: inventory matching from fully homomorphic encryption
Topological Portfolio Selection and Optimization
Customer-Category Interest Model: A Graph-Based Collaborative Filtering Model with Applications in Finance
Optimizing Sequential Predictions for Order Execution: a Decision Focused Learning Approach
GoSage: Heterogeneous Graph Neural Network Using Hierarchical Attention for Collusion Fraud Detection
Connecting the dots: forecasting and explaining short-term market volatility
Dynamic Pricing in Securities Lending Market: Application in Revenue Optimization for an Agent Lender Portfolio
Dealing with transaction costs in portfolio optimization: online gradient descent with momentum
SURF: improving classifiers in production by learning from busy and noisy end users
Adversarial attacks on machine learning systems for high-frequency trading
A Fast Non-Linear Coupled Tensor Completion Algorithm for Financial Data Integration and Imputation
Dark-Pool Smart Order Routing: a Combinatorial Multi-armed Bandit Approach
Is Small Really Beautiful for Central Bank Communication? Evaluating Language Models for Finance: Llama-3-70B, GPT-4, FinBERT-FOMC, FinBERT, and VADER
Autoregressive DRL with Learned Intrinsic Rewards for Portfolio Optimisation
The GANfather: Controllable generation of malicious activity to improve defence systems
FinDKG: Dynamic Knowledge Graphs with Large Language Models for Detecting Global Trends in Financial Markets
Offline Deep Reinforcement Learning for Dynamic Pricing of Consumer Credit
Multireference Alignment for Lead-Lag Detection in Multivariate Time Series and Equity Trading
FlowMind: Automatic Workflow Generation with LLMs
Synthesizing credit card transactions
CVA Hedging with Reinforcement Learning
Conservative Predictions on Noisy Financial Data
Quantifying ESG alpha using scholar big data: an automated machine learning approach
GARCH-Informed Neural Networks for Volatility Prediction in Financial Markets
TeGraF: temporal and graph based fraudulent transaction detection framework
Privacy-preserving portfolio pricing
Interactions of market making algorithms: a study on perceived collusion
Risk-sensitive reinforcement learning: a martingale approach to reward uncertainty
Denoising Diffusion Probabilistic Model for Realistic Financial Correlation Matrices
TABCF: Counterfactual Explanations for Tabular Data Using a Transformer-Based VAE
Paying down metadata debt: learning the representation of concepts using topic models
A hybrid model for forecasting short-term electricity demand
Detecting Financial Market Manipulation with Statistical Physics Tools
Learning FX trading strategies with FQI and persistent actions
A Financial Market Simulation Environment for Trading Agents Using Deep Reinforcement Learning
Collusion Resistant Federated Learning with Oblivious Distributed Differential Privacy
FinRL: deep reinforcement learning framework to automate trading in quantitative finance
Sequential Banking Products Recommendation and User Profiling in One Go
Machine learning fund categorizations
TGEditor: Task-Guided Graph Editing for Augmenting Temporal Financial Transaction Networks
Unveiling Recurring Financial Patterns: Novel unsupervised filtering algorithms for enhanced forecasting
An automated portfolio trading system with feature preprocessing and recurrent reinforcement learning
Improved predictive deep temporal neural networks with trend filtering
Stock Recommendations for Individual Investors: A Temporal Graph Network Approach with Mean-Variance Efficient Sampling
Adaptive Risk-Based Control in Financial Trading
A GANs-Based Approach for Stock Price Anomaly Detection and Investment Risk Management
FairNNV: The Neural Network Verification Tool For Certifying Fairness
DRL Trading with CPT Actor and Truncated Quantile Critics
A Generative Approach for Comprehensive Financial Event Extraction at the Document Level
FISHNET: Financial Intelligence from Sub-querying, Harmonizing, Neural-Conditioning, Expert Swarms, and Task Planning
A multi-faceted approach to large scale financial forecasting
Investor behavior modeling by analyzing financial advisor notes: a machine learning perspective
Model-Agnostic Pricing of Exotic Derivatives Using Signatures
Differentially private secure multi-party computation for federated learning in financial applications
Analyzing Cascading Outbreak of GameStop Event: A Practical Approach Using Network Analysis and Large Language Models
Macroeconomic Conditioned Synthetic Financial Markets
Deep Learning for Systemic Risk Measures
Learning Mutual Fund Categorization using Natural Language Processing
Enhancing Financial Question Answering with a Multi-Agent Reflection Framework
Graph Feature Preprocessor: Real-time Subgraph-based Feature Extraction for Financial Crime Detection
Cost-Efficient Reinforcement Learning for Optimal Trade Execution on Dynamic Market Environment
Multi-agent reinforcement learning in a realistic limit order book market simulation
FinBERT-FOMC: Fine-Tuned FinBERT Model with Sentiment Focus Method for Enhancing Sentiment Analysis of FOMC Minutes
FinVision: A Multi-Agent Framework for Stock Market Prediction
EX-DRL: Hedging Against Heavy Losses with EXtreme Distributional Reinforcement Learning
Mapping of Financial Services datasets using Human-in-the-Loop
A Dutch Financial Large Language Model
Rolling Forward: Enhancing LightGCN with Causal Graph Convolution for Credit Bond Recommendation
Efficient Calibration of Multi-Agent Simulation Models from Output Series with Bayesian Optimization
Threat Class Predictor: An explainable framework for predicting vulnerability threat using topic and trend modeling
PEVuln: A Benchmark Dataset for Using Machine Learning to Detect Vulnerabilities in PE Malware
Proxy in a Haystack: Uncovering and Classifying MFA Bypass Phishing Attacks in Large-Scale Authentication Data
Small Effect Sizes in Malware Detection? Make Harder Train/Test Splits!
Proceedings of the Conference on Applied Machine Learning in Information Security (CAMLIS 2024), Arlington, Virginia, USA, October 24-25, 2024
Temporal Attack Detection in Multimodal Cyber-Physical Systems with Sticky HDP-HMM
Proceedings of the Conference on Applied Machine Learning in Information Security, CAMLIS 2022, Arlington, Virginia, USA, October 20-21, 2022
Navigating Concept Drift and Packing Complexity in Malware Family Classification
Adaptive Experimental Design for Intrusion Data Collection
Defending Large Language Models Against Attacks With Residual Stream Activation Analysis
Efficient Malware Analysis Using Metric Embeddings
AdapterSwap: Continuous Training of LLMs with Data Removal and Access-Control Guarantees
Towards autonomous cyber-defence: using co-operative decision making for cybersecurity
FASER: Binary Code Similarity Search through the use of Intermediate Representations
MalDICT: Benchmark Datasets on Malware Behaviors, Platforms, Exploitation, and Packers
Minimizing Compute Costs: When Should We Run More Expensive Malware Analysis?
Embedding-based classifiers can detect prompt injection attacks
Proceedings of the Conference on Applied Machine Learning in Information Security, Arlington, Virginia, USA, October 19-20, 2023
Half-Day Vulnerabilities: A study of the First Days of CVE Entries
Applying Action Masking and Curriculum Learning Techniques to Improve Data Efficiency and Overall Performance in Operational Technology Cyber Security using Reinforcement Learning
Firenze: Model Evaluation Using Weak Signals
Ransomware Evolution: Unveiling Patterns Using HDBSCAN
Curl: Private LLMs through Wavelet-Encoded Look-Up Tables
Binary Malware Attribution using LLM Embeddings and Topological Data Analysis
Model Leeching: An Extraction Attack Targeting LLMs
Enhancing Exfiltration Path Analysis Using Reinforcement Learning
Defending the unknown: Exploring reinforcement learning agents' deployment in realistic, unseen networks
Network Security Modelling with Distributional Data
LLM agents for vulnerability identification and verification of CVEs
Anomaly Detection of Command Shell Sessions based on DistilBERT: Unsupervised and Supervised Approaches
Multi-Agent Reinforcement Learning for Maritime Operational Technology Cyber Security
PyRIT: A Framework for Security Risk Identification and Red Teaming in Generative AI Systems
Web Content Filtering Through Knowledge Distillation of Large Language Models
Is 퐹1 Score Suboptimal for Cybersecurity Models? Introducing 퐶푠푐표푟푒, a Cost-Aware Alternative for Model Assessment
Defending Against Indirect Prompt Injection Attacks With Spotlighting
DIP-ECOD: Improving Anomaly Detection in Multimodal Distributions
Learning to Embed Byte Sequences with Convolutional Autoencoders
Detecting SQL Injection Attacks using Machine Learning
Inroads into Autonomous Network Defence using Explained Reinforcement Learning
Quantum Machine Learning for Join Order Optimization using Variational Quantum Circuits
Enhancing data quality and process optimization for smart manufacturing lines in industry 4.0 scenarios
Sensor fusion on the edge: initial experiments in the EdgeServe system
Proceedings of the International Workshop on Big Data in Emergent Distributed Environments, BiDEDE 2024, Santiago, Chile, June 9-15, 2024